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A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control (2024)
Conference Proceeding
Montague, K., Hart, E., & Paechter, B. (2024). A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I (178-193). https://doi.org/10.1007/978-3-031-56852-7_12

Behaviour trees (BTs) are commonly used as controllers in robotic swarms due their modular composition and to the fact that they can be easily interpreted by humans. From an algorithmic perspective, an additional advantage is that extra modules can e... Read More about A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control.

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Conference Proceeding
Montague, K., Hart, E., Paechter, B., & Nitschke, G. (2023). A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation: 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (145-160). https://doi.org/10.1007/978-3-031-30229-9_10

Designing controllers for a swarm of robots such that collabo-rative behaviour emerges at the swarm level is known to be challenging. Evolutionary approaches have proved promising, with attention turning more recently to evolving repertoires of dive... Read More about A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms.

On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture (2023)
Conference Proceeding
Lupión, M., Cruz, N. C., Paechter, B., & Ortigosa, P. M. (2023). On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture. In Metaheuristics: 14th International Conference, MIC 2022, Syracuse, Italy, July 11–14, 2022, Proceedings (133-142). https://doi.org/10.1007/978-3-031-26504-4_10

Neural networks stand out in Artificial Intelligence for their capacity of being applied to multiple challenging tasks such as image classification. However, designing a neural network to address a particular problem is also a demanding task that req... Read More about On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture.

Accelerating neural network architecture search using multi-GPU high-performance computing (2022)
Journal Article
Lupión, M., Cruz, N. C., Sanjuan, J. F., Paechter, B., & Ortigosa, P. M. (2023). Accelerating neural network architecture search using multi-GPU high-performance computing. Journal of Supercomputing, 79, 7609-7625. https://doi.org/10.1007/s11227-022-04960-z

Neural networks stand out from artificial intelligence because they can complete challenging tasks, such as image classification. However, designing a neural network for a particular problem requires experience and tedious trial and error. Automating... Read More about Accelerating neural network architecture search using multi-GPU high-performance computing.

A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics (2021)
Book Chapter
Stone, C., Hart, E., & Paechter, B. (2021). A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics. In N. Pillay, & R. Qu (Eds.), Automated Design of Machine Learning and Search Algorithms (91-107). Springer. https://doi.org/10.1007/978-3-030-72069-8_6

Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, usually rely on a set of domain-specific low-level heuristics which exist below the domain-barrier and are manipulated by the hyper-heuristic itself. However, for... Read More about A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics.

Evolving planar mechanisms for the conceptual stage of mechanical design (2019)
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2019). Evolving planar mechanisms for the conceptual stage of mechanical design. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (383-384). https://doi.org/10.1145/3319619.3322006

This study presents a method to evolve planar mechanism prototypes using an evolutionary computing approach. Ultimately, the idea is to provide drafts for designers at the conceptual design stage of mechanism design which meet their design brief. The... Read More about Evolving planar mechanisms for the conceptual stage of mechanical design.

Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes (2019)
Journal Article
Ferrández, M. R., Redondo, J. L., Ivorra, B., Ramos, A. M., Ortigosa, P. M., & Paechter, B. (2020). Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes. Engineering Optimization, 52(5), 896-913. https://doi.org/10.1080/0305215x.2019.1618289

This work focuses on the optimization of some high-pressure and temperature food treatments. In some cases, when dealing with real-life multi-objective optimization problems, such as the one considered here, the computational cost of evaluating the c... Read More about Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes.

2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms (2018)
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2019). 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. In H. Rodrigues, J. Herskovits, C. Mota Soares, A. Araújo, J. Guedes, J. Folgado, …J. Madeira (Eds.), EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization (926-937). https://doi.org/10.1007/978-3-319-97773-7_80

In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A specific area of mechanical design focuses on planar mechanisms. These are a... Read More about 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms.

On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains (2018)
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2018). On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. In Parallel Problem Solving from Nature – PPSN XV 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part I. https://doi.org/10.1007/978-3-319-99253-2_14

Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, rely on a set of domain-specific low-level heuristics at lower levels. For some domains, there is a lack of available heuristics, while for novel problems, no heur... Read More about On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains.

Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm (2018)
Conference Proceeding
Hart, E., Steyven, A. S. W., & Paechter, B. (2018). Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. In GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference (101-108). https://doi.org/10.1145/3205455.3205481

The presence of functionality diversity within a group has been demonstrated to lead to greater robustness, higher performance and increased problem-solving ability in a broad range of studies that includes insect groups, human groups and swarm robot... Read More about Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm.

Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs (2018)
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2018). Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. In Applications of Evolutionary Computation (578-593). https://doi.org/10.1007/978-3-319-77538-8_40

In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heuristics often suffice in this case. However, for many domains, a simple heurist... Read More about Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs.

Evaluation of a genetic representation for outline shapes (2017)
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2017). Evaluation of a genetic representation for outline shapes. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference Companion (1419-1422). https://doi.org/10.1145/3067695.3082501

This work in progress focuses on the evaluation of a genetic representation for outline shapes for planar mechanical levers which addresses the first stage of the complex real-world problem of modelling and evolving planar mechanical lever systems. T... Read More about Evaluation of a genetic representation for outline shapes.

On the comparison of initialisation strategies in differential evolution for large scale optimisation (2017)
Journal Article
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018). On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z

Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works have studied the effects that a population initialisation strategy has on... Read More about On the comparison of initialisation strategies in differential evolution for large scale optimisation.

An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics (2017)
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2017). An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference (155-162). https://doi.org/10.1145/3071178.3071232

A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. However, the role played by the environment in influencing the effectiveness o... Read More about An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics.

Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation (2016)
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016). Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016 (296-305). https://doi.org/10.1007/978-3-319-50349-3_25

Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic which can apply one of two meta-heuristics at the current stage of the search.... Read More about Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation.

Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems (2016)
Conference Proceeding
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016). Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2016.7743969

In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control scheme based on both Fuzzy Logic Controllers (FLCs) and Hyper-heuristics (HHs).... Read More about Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems.

Trickle-Plus: Elastic Trickle algorithm for Low-power networks and Internet of Things (2016)
Conference Proceeding
Ghaleb, B., Al-Dubai, A., Ekonomou, E., Paechter, B., & Qasem, M. (2016). Trickle-Plus: Elastic Trickle algorithm for Low-power networks and Internet of Things. In Wireless Communications and Networking Conference (WCNC), 2016 IEEE (1-6). https://doi.org/10.1109/WCNC.2016.7564654

Constrained Low-power and Lossy networks (LLNs) represent the building block for the ever-growing Internet of Things (IoT) that deploy the Routing Protocol for Low Power and Lossy networks (RPL) as a key routing standard. RPL, along with other routin... Read More about Trickle-Plus: Elastic Trickle algorithm for Low-power networks and Internet of Things.

Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm (2016)
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2016). Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In Parallel Problem Solving from Nature – PPSN XIV; Lecture Notes in Computer Science (921-931). https://doi.org/10.1007/978-3-319-45823-6_86

It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear exactly how parameterisation of a given environment might influence the emer... Read More about Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm.

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems (2016)
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV (134-144). https://doi.org/10.1007/978-3-319-45823-6_13

We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds Optimisation (mbo) and Multi-leader Migrating Birds Optimisation (mmbo), t... Read More about Analysing the performance of migrating birds optimisation approaches for large scale continuous problems.

Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. (2015)
Conference Proceeding
Hart, E., Steyven, A., & Paechter, B. (2015). Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15 (169-176). https://doi.org/10.1145/2739480.2754688

Ensuring the integrity of a robot swarm in terms of maintaining a stable population of functioning robots over long periods of time is a mandatory prerequisite for building more complex systems that achieve user-defined tasks. mEDEA is an environ... Read More about Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication..

The Cost of Communication: Environmental Pressure and Survivability in mEDEA (2015)
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2015). The Cost of Communication: Environmental Pressure and Survivability in mEDEA. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion '15 (1239-1240). https://doi.org/10.1145/2739482.2768489

We augment the mEDEA algorithm to explicitly account for the costs of communication between robots. Experimental results show that adding a costs for communication exerts environmental pressure to implicitly select for genomes that maintain high... Read More about The Cost of Communication: Environmental Pressure and Survivability in mEDEA.

A Lifelong Learning Hyper-heuristic Method for Bin Packing (2015)
Journal Article
Hart, E., Sim, K., & Paechter, B. (2015). A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121

We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; representative problems and heur... Read More about A Lifelong Learning Hyper-heuristic Method for Bin Packing.

Learning to solve bin packing problems with an immune inspired hyper-heuristic. (2013)
Conference Proceeding
Sim, K., Hart, E., & Paechter, B. (2013). Learning to solve bin packing problems with an immune inspired hyper-heuristic. In P. Liò, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life, ECAL 2013 (856-863). https://doi.org/10.7551/978-0-262-31709-2-ch126

Motivated by the natural immune system's ability to defend the body by generating and maintaining a repertoire of antibodies that collectively cover the potential pathogen space, we describe an artificial system that discovers and maintains a reperto... Read More about Learning to solve bin packing problems with an immune inspired hyper-heuristic..

A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution. (2012)
Conference Proceeding
Sim, K., Hart, E., & Paechter, B. (2012). A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution. In Parallel Problem Solving from Nature: PPSN XII (348-357). https://doi.org/10.1007/978-3-642-32964-7_35

A hyper-heuristic for the one dimensional bin packing problem is presented that uses an Evolutionary Algorithm (EA) to evolve a set of attributes that characterise a problem instance. The EA evolves divisions of variable quantity and dimension that r... Read More about A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution..

This pervasive day: creative Interactive methods for encouraging public engagement with FET research (2011)
Journal Article
Helgason, I., Bradley, J., Egan, C., Paechter, B., & Hart, E. (2011). This pervasive day: creative Interactive methods for encouraging public engagement with FET research. Procedia Computer Science, 7, 207-208. https://doi.org/10.1016/j.procs.2011.09.028

This paper describes a case study of a programme of interactive public engagement activities presented by the PerAda Co-ordination Action project (FET Proactive Initiative on Pervasive Adaptation) [1] in 2011. The intention behind these events was to... Read More about This pervasive day: creative Interactive methods for encouraging public engagement with FET research.

Representations and evolutionary operators for the scheduling of pump operations in water distribution networks. (2011)
Journal Article
Lopez-Ibanez, M., Tumula, P., & Paechter, B. (2011). Representations and evolutionary operators for the scheduling of pump operations in water distribution networks. Evolutionary Computation, 19, 429-467. https://doi.org/10.1162/EVCO_a_00035

Reducing the energy consumption of water distribution networks has never had more significance. The greatest energy savings can be obtained by carefully scheduling the operations of pumps. Schedules can be defined either implicitly, in terms of other... Read More about Representations and evolutionary operators for the scheduling of pump operations in water distribution networks..

Heaven and Hell: visions for pervasive adaptation (2011)
Journal Article
Paechter, B., Pitt, J., Serbedzija, N., Michael, K., Willies, J., & Helgason, I. (2011). Heaven and Hell: visions for pervasive adaptation. Procedia Computer Science, 7, 81-82. https://doi.org/10.1016/j.procs.2011.12.025

With everyday objects becoming increasingly smart and the “info-sphere” being enriched with nano-sensors and networked to computationally-enabled devices and services, the way we interact with our environment has changed significantly, and will conti... Read More about Heaven and Hell: visions for pervasive adaptation.

Towards self-aware PerAda systems. (2010)
Conference Proceeding
Hart, E., & Paechter, B. (2010). Towards self-aware PerAda systems. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010 Proceedings (314-216). https://doi.org/10.1007/978-3-642-14547-6_28

Pervasive Adaptation (PerAda) refers to massive-scale pervasive information and communication systems which are capable of autonomously adapting to highly dynamic and open technological and user contexts. PerAda systems are thus a special case of col... Read More about Towards self-aware PerAda systems..

Strengthening the Forward Variable Selection Stopping Criterion (2009)
Conference Proceeding
Herrera, L. J., Rubio, G., Pomares, H., Paechter, B., Guillén, A., & Rojas, I. (2009). Strengthening the Forward Variable Selection Stopping Criterion. In Artificial Neural Networks – ICANN 2009 (215-224). https://doi.org/10.1007/978-3-642-04277-5_22

Given any modeling problem, variable selection is a preprocess step that selects the most relevant variables with respect to the output variable. Forward selection is the most straightforward strategy for variable selection; its application using the... Read More about Strengthening the Forward Variable Selection Stopping Criterion.

Parallelization of the nearest-neighbour search and the cross-validation error evaluation for the kernel weighted k-nn algorithm applied to large data dets in matlab (2009)
Conference Proceeding
Rubio, G., Guillen, A., Pomares, H., Rojas, I., Paechter, B., Glosekotter, P., & Torres-Ceballos, C. I. (2009). Parallelization of the nearest-neighbour search and the cross-validation error evaluation for the kernel weighted k-nn algorithm applied to large data dets in matlab. In HPCS '09. International Conference on High Performance Computing & Simulation, 2009. https://doi.org/10.1109/hpcsim.2009.5192804

The kernel weighted k-nearest neighbours (KWKNN) algorithm is an efficient kernel regression method that achieves competitive results with lower computational complexity than Least-Squares Support Vector Machines and Gaussian Processes. This paper pr... Read More about Parallelization of the nearest-neighbour search and the cross-validation error evaluation for the kernel weighted k-nn algorithm applied to large data dets in matlab.

Setting the research agenda in automated timetabling: the second international timetabling competition (2009)
Journal Article
McCollum, B., Schaerf, A., Paechter, B., McMulan, P., Lewis, R. M. R., Parkes, A. J., …Burke, E. (2010). Setting the research agenda in automated timetabling: the second international timetabling competition. INFORMS Journal on Computing, 22, 120-130. https://doi.org/10.1287/ijoc.1090.0320

The Second International Timetabling Competition (TTC2007) opened in August 2007. Building on the success of the first competition in 2002, this sequel aimed to further develop research activity in the area of educational timetabling. The broad aim o... Read More about Setting the research agenda in automated timetabling: the second international timetabling competition.

Parallel Optimisation of Pump Schedules with a Thread-Safe Variant of EPANET Toolkit (2009)
Conference Proceeding
López-Ibáñez, M., Prasad, D. T., & Paechter, B. (2009). Parallel Optimisation of Pump Schedules with a Thread-Safe Variant of EPANET Toolkit. In Water Distribution Systems Analysis 2008. https://doi.org/10.1061/41024%28340%2940

The optimisation of pump operations in water distribution networks is an ongoing research topic motivated by the great energy savings that a careful scheduling of pumps may achieve. State-of-the-art approaches often combine an optimisation algorithm,... Read More about Parallel Optimisation of Pump Schedules with a Thread-Safe Variant of EPANET Toolkit.

Computing the State of Specknets: an immune-inspired approach. (2009)
Conference Proceeding
Davoudani, D., Hart, E., & Paechter, B. (2009). Computing the State of Specknets: an immune-inspired approach. In Performance Evaluation of Computer and Telecommunication Systems, 2008. SPECTS 2008. International Symposium on (52-59)

Speckled Computing is an emerging technology based on the deployment of thousands of minute semiconductor grains in dense, wireless networks known as Specknets. Specknets collect and process data to achieve some application dependent functionalit... Read More about Computing the State of Specknets: an immune-inspired approach..

Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks (2008)
Journal Article
López-Ibáñez, M., Prasad, T. D., & Paechter, B. (2008). Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks. Journal of Water Resources Planning and Management, 134, 337-346. https://doi.org/10.1061/%28ASCE%290733-9496%282008%29134%3A4%28337%29

Reducing energy consumption of water distribution networks has never had more significance than today. The greatest energy savings can be obtained by careful scheduling of operation of pumps. Schedules can be defined either implicitly, in terms of ot... Read More about Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks.

Computing the State of Specknets: further analysis of an innate immune-inspired model. (2008)
Conference Proceeding
Davoudani, D., Hart, E., & Paechter, B. (2008). Computing the State of Specknets: further analysis of an innate immune-inspired model. In P. Bentley, D. Lee, & S. Jung (Eds.), Artificial Immune Systems, 7th International Conference, ICARIS 2008, Phuket, Thailand, August 2008, Proceedings (95-106). https://doi.org/10.1007/978-3-540-85072-4

Specknets consist of hundreds of miniature devices, which are each capable of processing data and communicating wirelessly across short distances. Such networks, with their great complexity, pose considerable challenges for engineers due to the unrel... Read More about Computing the State of Specknets: further analysis of an innate immune-inspired model..

Boosting the Immune System (2008)
Conference Proceeding
McEwan, C., Hart, E., & Paechter, B. (2008). Boosting the Immune System. In Artificial Immune Systems (316-327). https://doi.org/10.1007/978-3-540-85072-4_28

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or modelling biologically plausible dynamical systems, with little overlap between. Although the balance is la... Read More about Boosting the Immune System.

A Conflict Tabu Search Evolutionary Algorithm for Solving Constraint Satisfaction Problems (2008)
Conference Proceeding
Craenen, B. G. W., & Paechter, B. (2008). A Conflict Tabu Search Evolutionary Algorithm for Solving Constraint Satisfaction Problems. In Evolutionary Computation in Combinatorial Optimization (13-24). https://doi.org/10.1007/978-3-540-78604-7_2

This paper introduces a hybrid Tabu Search - Evolutionary Algorithm for solving the binary constraint satisfaction problem, called CTLEA. A continuation of an earlier introduced algorithm, called the STLEA, the CTLEA replaces the earlier compound lab... Read More about A Conflict Tabu Search Evolutionary Algorithm for Solving Constraint Satisfaction Problems.

Revisiting the Central and Peripheral Immune System (2007)
Conference Proceeding
McEwan, C., Hart, E., & Paechter, B. (2007). Revisiting the Central and Peripheral Immune System. In Artificial Immune Systems. ICARIS 2007 (240-251). https://doi.org/10.1007/978-3-540-73922-7_21

The idiotypic network has a long and chequered history in both theoretical immunology and Artificial Immune Systems. In terms of the latter, the drive for engineering applications has led to a diluted interpretation of the immunological models. Resea... Read More about Revisiting the Central and Peripheral Immune System.

An Immune-Inspired Approach to Speckled Computing (2007)
Conference Proceeding
Davoudani, D., Hart, E., & Paechter, B. (2007). An Immune-Inspired Approach to Speckled Computing. In L. de Castro, F. Von Zuben, & H. Knidel (Eds.), Artificial Immune Systems. ICARIS 2007 (288-299). https://doi.org/10.1007/978-3-540-73922-7_25

Speckled Computing offers a radically new concept in information technology that has the potential to revolutionise the way we communicate and exchange information. Specks — minute, autonomous, semi-conductor grains that can sense and compute locally... Read More about An Immune-Inspired Approach to Speckled Computing.

Ensemble: embodied experiences in a sound and jewellery installation (2007)
Conference Proceeding
Kettley, S., Smyth, M., Arvind, D. K., Greig, F., McGregor, I., & Paechter, B. (2007). Ensemble: embodied experiences in a sound and jewellery installation. In D. Golightly, T. Rose, & B. Light (Eds.), Create 07 Creative Inventions, Innovations and Everyday Designs in HCI

ensemble - an interactive collection of networked jewellery with gesturally determined, real time sonic output

Boosting the Performance of a Multiobjective Algorithm to Design RBFNNs Through Parallelization (2007)
Conference Proceeding
Guillen, A., Rojas, I., Gonzalez, J., Pomares, H., Herrera, L. J., & Paechter, B. (2007). Boosting the Performance of a Multiobjective Algorithm to Design RBFNNs Through Parallelization. In Adaptive and Natural Computing Algorithms, 8th International Conference, ICANNGA 2007 (85-92). https://doi.org/10.1007/978-3-540-71618-1_10

Radial Basis Function Neural Networks (RBFNNs) have been widely used to solve classification and regression tasks providing satisfactory results. The main issue when working with RBFNNs is how to design them because this task requires the optimizatio... Read More about Boosting the Performance of a Multiobjective Algorithm to Design RBFNNs Through Parallelization.

Empirical Validation of a Gossiping Communication Mechanism for Parallel EAs (2007)
Conference Proceeding
Laredo, J. L. J., Castillo, P. A., Paechter, B., Mora, A. M., Alfaro-Cid, E., Esparcia-Alcazar, A. I., & Merelo, J. J. (2007). Empirical Validation of a Gossiping Communication Mechanism for Parallel EAs. In Applications of Evolutionary Computing: EvoWorkshops 2007 (129-136)

The development of Peer-to-Peer (P2P) systems is still a challenge due to the huge number of factors involved. Validation of these systems must be defined in terms of describing the adequacy of the P2P model to the actual environment. This paper focu... Read More about Empirical Validation of a Gossiping Communication Mechanism for Parallel EAs.

Finding feasible timetables using group-based operators. (2007)
Journal Article
Lewis, R. M. R., & Paechter, B. (2007). Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation, 11, 397-413. https://doi.org/10.1109/TEVC.2006.885162

This paper describes the applicability of the so-called "grouping genetic algorithm" to a well-known version of the university course timetabling problem. We note that there are, in fact, various scaling up issues surrounding this sort of algorithm a... Read More about Finding feasible timetables using group-based operators..

Metaheuristics for university course timetabling. (2007)
Book Chapter
Lewis, R. M. R., Paechter, B., & Rossi-Doria, O. (2007). Metaheuristics for university course timetabling. In K. Dahal, K. Chen Tan, & P. Cowling (Eds.), Evolutionary Scheduling (237-272). Berlin / Heidelberg: Springer. https://doi.org/10.1007/978-3-540-48584-1_9

In this chapter we consider the NP-complete problem of university course timetabling. We note that it is often difficult to gain a deep understanding of these sorts of problems due to the fact that so many different types of constraints can ultima... Read More about Metaheuristics for university course timetabling..

Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation (2006)
Conference Proceeding
Guillen, A., Rojas, I., Gonzalez, J., Pomares, H., Herrera, L. J., & Paechter, B. (2006). Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation. In AI 2006: Advances in Artificial Intelligence (1127-1132). https://doi.org/10.1007/11941439_135

Nature shows many examples where the specialisation of elements aimed to solve different problems is successful. There are explorer ants, worker bees, etc., where a group of individuals is assigned a specific task. This paper will extrapolate this ph... Read More about Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation.

A tabu search evolutionary algorithm for solving constraint satisfaction problems. (2006)
Conference Proceeding
Craenen, B. G. W., & Paechter, B. (2006). A tabu search evolutionary algorithm for solving constraint satisfaction problems. In Parallel Problem Solving from Nature - PPSN IX (152-161). https://doi.org/10.1007/11844297_16

The paper introduces a hybrid Tabu Search-Evolutionary Algorithm for solving the constraint satisfaction problem, called STLEA. Extensive experimental fine-tuning of parameters of the algorithm was performed to optimise the performance of the algorit... Read More about A tabu search evolutionary algorithm for solving constraint satisfaction problems..

A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS (2006)
Journal Article
Baños, R., Gil, C., Paechter, B., & Ortega, J. (2007). A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS. Journal of Mathematical Modelling and Algorithms, 6(2), 213-230. https://doi.org/10.1007/s10852-006-9041-6

Real optimization problems often involve not one, but multiple objectives, usually in conflict. In single-objective optimization there exists a global optimum, while in the multi-objective case no optimal solution is clearly defined but rather a set... Read More about A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS.

Peer-to-peer networks for scalable grid landscapes in social agent simulations. (2005)
Conference Proceeding
Craenen, B. G. W., & Paechter, B. (2005). Peer-to-peer networks for scalable grid landscapes in social agent simulations. In Proceedings of the Artificial Intelligence and Social Behaviour Convention (AISB) 2005 (64-71)

Recently, peer-to-peer networks have been proposed as the underlying architecture of large scale distributed social agent simulations. A number of problems arise when grid landscapes are used to represent the landscape in these simulations, primarily... Read More about Peer-to-peer networks for scalable grid landscapes in social agent simulations..

Application of the Grouping Genetic Algorithm to University Course Timetabling (2005)
Conference Proceeding
Lewis, R., Lewis, R. M. R., & Paechter, B. (2005). Application of the Grouping Genetic Algorithm to University Course Timetabling. In J. Gottlieb, & G. Raidl (Eds.), Evolutionary Computation in Combinatorial Optimization (144-153). https://doi.org/10.1007/978-3-540-31996-2_14

University Course Timetabling-Problems (UCTPs) involve the allocation of resources (such as rooms and timeslots) to all the events of a university, satisfying a set of hard-constraints and, as much as possible, some soft constraints. Here we work wit... Read More about Application of the Grouping Genetic Algorithm to University Course Timetabling.

Parallelization of population-based multi-objective meta-heuristics: An empirical study (2005)
Journal Article
Baños, R., Gil, C., Paechter, B., & Ortega, J. (2006). Parallelization of population-based multi-objective meta-heuristics: An empirical study. Applied Mathematical Modelling, 30(7), 578-592. https://doi.org/10.1016/j.apm.2005.05.021

In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneously optimize all the objectives. However, the majority of this kind of pro... Read More about Parallelization of population-based multi-objective meta-heuristics: An empirical study.

An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case. (2005)
Conference Proceeding
Lewis, R., & Paechter, B. (2005). An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case. In 2005 IEEE Congress on Evolutionary Computation (2856-2863). https://doi.org/10.1109/cec.2005.1555053

A grouping genetic algorithm (GGA) for the university course timetabling problem is outlined. We propose six different fitness functions, all sharing the same common goal, and look at the effects that these can have on the algorithm with respect to b... Read More about An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case..

Maintaining Connectivity in a Scalable and Robust Distributed Environment (2005)
Conference Proceeding
Jelasity, M., Preuss, M., van Steen, M., & Paechter, B. (2005). Maintaining Connectivity in a Scalable and Robust Distributed Environment. In H. E. Bal, K. P. Lohr, & A. Reinfeld (Eds.), 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02) (389-394). https://doi.org/10.1109/CCGRID.2002.1017166

This paper describes a novel peer-to-peer (P2P) environment for running distributed Java applications on the Internet. The possible application areas include simple load balancing, parallel evolutionary computation, agent-based simulation and artific... Read More about Maintaining Connectivity in a Scalable and Robust Distributed Environment.

Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2. (2005)
Conference Proceeding
Lopez-Ibanez, M., Devi Prasad, T., & Paechter, B. (2005). Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2. . https://doi.org/10.1109/CEC.2005.1554716

Significant operational cost and energy savings can be achieved by optimising the schedules of pumps, which pump water from source reservoirs to storage tanks, in water distribution networks. Despite the fact that pump scheduling problem involves sev... Read More about Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2..

New crossover operators for timetabling with evolutionary algorithms. (2004)
Conference Proceeding
Lewis, R. M. R., & Paechter, B. (2004). New crossover operators for timetabling with evolutionary algorithms. In A. Lotfi (Ed.), 5th International Conference on Recent Advances in Soft Computing (189-195)

When using an evolutionary algorithm (EA) to optimise a population of feasible course timetables, it is important that the mutation and crossover operators are designed in such a way so that they don?t produce unfeasible or illegal offspring. In this... Read More about New crossover operators for timetabling with evolutionary algorithms..

PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation (2004)
Journal Article
de Toro Negro, F., Ortega, J., Ros, E., Mota, S., Paechter, B., & Martin, J. M. (2004). PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation. Parallel Computing, 30(5-6), 721-739. https://doi.org/10.1016/j.parco.2003.12.012

This paper deals with the study of the cooperation between parallel processing and evolutionary computation to obtain efficient procedures for solving multiobjective optimisation problems. We propose a new algorithm called PSFGA (parallel single fron... Read More about PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation.

Improving vehicle routing using a customer waiting time colony. (2004)
Conference Proceeding
Sa'adah, S., Ross, P., & Paechter, B. (2004). Improving vehicle routing using a customer waiting time colony. In J. Gottlieb, & G. Raidl (Eds.), Evolutionary Computation in Combinatorial Optimization (188-198). https://doi.org/10.1007/978-3-540-24652-7_19

In the vehicle routing problem with time windows (VRPTW), there are two main objectives. The primary objective is to reduce the number of vehicles, the secondary one is to minimise the total distance travelled by all vehicles. This paper describes so... Read More about Improving vehicle routing using a customer waiting time colony..

Routing using evolutionary agents and proactive transitions. (2003)
Book Chapter
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2003). Routing using evolutionary agents and proactive transitions. In Applications of Evolutionary Computing (696-705). Springer-Verlag

The authors have previously introduced the concept of building a delivery network using an agent-based system. The delivery networks are built in response to a real-world problem that involves delivering post to a large number of households within an... Read More about Routing using evolutionary agents and proactive transitions..

A comparison of the performance of different metaheuristics on the timetabling problem. (2003)
Conference Proceeding
Rossi-Doria, O., Sampels, M., Birattari, M., Chiarandini, M., Dorigo, M., Gambardella, L. M., …Stutzle, T. (2003). A comparison of the performance of different metaheuristics on the timetabling problem. In E. Burke, & P. Causmaecker (Eds.), Practice and Theory of AutomatedTimetabling IV (329-351). https://doi.org/10.1007/978-3-540-45157-0_22

The main goal of this paper is to attempt an unbiased comparison of the performance of straightforward implementations of five different metaheuristics on a university course timetabling problem. In particular, the metaheuristics under consideration... Read More about A comparison of the performance of different metaheuristics on the timetabling problem..

A scaleable and robust framework for distributed application. (2002)
Journal Article
Jelasity, M., Preuss, M., & Paechter, B. (2002). A scaleable and robust framework for distributed application. World Congress on Computational Intelligence, 2, 1540-1545

This paper describes a novel tool for running distributed experiments on the Internet. The possible applications include simple load balancing, parallel evolutionary computation, agent-based simulation and artificial life. Our environment is based on... Read More about A scaleable and robust framework for distributed application..

Maintaining connectivity in a scaleable and robust distributed environment. (2002)
Journal Article
Jelasity, M., Preuss, M., Van Steen, M., & Paechter, B. (2002). Maintaining connectivity in a scaleable and robust distributed environment. Cluster Computing and the Grid, 389-394. https://doi.org/10.1109/CCGRID.2002.1017166

This paper describes a novel peer-to-peer (P2P) environment for running distributed Java applications on the Internet. The possible application areas include simple load balancing, parallel evolutionary computation, agent-based simulation and artific... Read More about Maintaining connectivity in a scaleable and robust distributed environment..

A GA evolving instructions for a timetable builder. (2002)
Conference Proceeding
Blum, C., Correia, S., Dorigo, M., Paechter, B., Rossi-Doria, O., & Snoek, M. (2002). A GA evolving instructions for a timetable builder. In E. Burke, & P. Causmaecker (Eds.), Proceedings of the Conference on the Practice and Theory of Automated Timetabling (PATAT 2002) (120-123)

In this work we present a Genetic Algorithm for tackling timetabling problems. Our approach uses an indirect solution representation, which denotes a number of instructions for a timetable builder on how to sequentially build a solution. These instru... Read More about A GA evolving instructions for a timetable builder..

A local search for the timetabling problem. (2002)
Conference Proceeding
Rossi-Doria, O., Blum, C., Knowles, J., Sampels, M., Socha, K., & Paechter, B. (2002). A local search for the timetabling problem. In E. Burke, & P. Causmaecker (Eds.), Proceedings of the Conference on the Practice and Theory of Automated Timetabling (PATAT 2002) (124-127)

This work is part of the Metaheuristic Network, a European Commission project that seeks to empirically compare the performance of various metaheuristics on different combinatorial optimization problems. In this paper we define a representation, a ne... Read More about A local search for the timetabling problem..

Solving a real world routing problem using multiple evolutionary algorithms. (2002)
Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002). Solving a real world routing problem using multiple evolutionary algorithms. In Parallel Problem Solving from Nature — PPSN VII (871-880). https://doi.org/10.1007/3-540-45712-7_84

This paper investigates the solving of a real world routing problem using evolutionary algorithms embedded within a Multi-agent system (MAS). An architecture for the MAS is proposed and mechanisms for controlling the interactions of agents are invest... Read More about Solving a real world routing problem using multiple evolutionary algorithms..

Solving a real world routing problem using evolutionary agents. (2002)
Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002). Solving a real world routing problem using evolutionary agents.

This paper investigates the solving of a real world routing problem using evolutionary algorithms embedded within a Multi-agent system (MAS). An architecture for the MAS is proposed and mechanisms for controlling the interactions of agents are invest... Read More about Solving a real world routing problem using evolutionary agents..

A framework for distributed evolutionary algorithms. (2002)
Conference Proceeding
Arenas, M. G., Collet, P., Eiben, A. E., Jeasity, M., Merelo Guervós, J. J., Paechter, B., …Schoenauer, M. (2002). A framework for distributed evolutionary algorithms. In 7th International Conference, Granada, Spain, September 7-11, 2002, Proceedings (665-675)

This paper describes the recently released DREAM (Distributed Resource Evolutionary Algorithm Machine) framework for the automatic distribution of evolutionary algorithm (EA) processing through a virtual machine built from large numbers of individual... Read More about A framework for distributed evolutionary algorithms..

A Scalable and Robust Framework for Distributed Applications (2002)
Conference Proceeding
Jelasity, M., Preuss, M., & Paechter, B. (2002). A Scalable and Robust Framework for Distributed Applications. In Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (1540-1545). https://doi.org/10.1109/CEC.2002.1004471

This paper describes a novel tool for running distributed experiments on the Internet. The possible applications include simple load balancing, parallel evolutionary computation, agent-based simulation and artificial life. Our environment is based on... Read More about A Scalable and Robust Framework for Distributed Applications.

A distributed resource evolutionary algorithm machine. (2002)
Conference Proceeding
Paechter, B., Baeck, T., Schoenauer, M., Eiben, A. E., Merelo Guervós, J. J., Sebag, M., & Fogarty, T. C. (2002). A distributed resource evolutionary algorithm machine. In Proceedings of the 2000 Congress on Evolutionary Computation, 2000 (951-958). https://doi.org/10.1109/CEC.2000.870746

This paper describes a project funded by the European Commission’ which seeks to provide the technology and software infrastructure necessary to support the next generation of evolving infohabitants in a way that makes that infrastructure univers... Read More about A distributed resource evolutionary algorithm machine..

A General Model for the Answer-Perturbation Techniques (2002)
Conference Proceeding
Stamate, D., Luchian, H., & Paechter, B. (2002). A General Model for the Answer-Perturbation Techniques. In Seventh International Working Conference on Scientific and Statistical Database Management (90-96). https://doi.org/10.1109/SSDM.1994.336958

Answer-perturbation techniques for the protection of statistical databases have been previously introduced (Luchian and Stamate, 1992); they are flexible (perturbation kept under control), modular (do not interact with the DBMS) techniques, which com... Read More about A General Model for the Answer-Perturbation Techniques.

Improving street based routing using building block mutations. (2002)
Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002). Improving street based routing using building block mutations. In J. Gottlieb, E. Hart, & S. Cagnoni (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN Kinsale, Ireland, April 3–4, 2002 Proceedings (189-202). https://doi.org/10.1007/3-540-46004-7_33

Street based routing (SBR) is a real-world inspired routing problem that builds routes within an urban area for mail deliveries. The authors have previously attempted to solve this problem using an Evolutionary Algorithm (EA). In this paper the autho... Read More about Improving street based routing using building block mutations..

Street-based routing using an evolutionary algorithm (2001)
Conference Proceeding
Urquhart, N. B., Paechter, B., & Chisholm, K. (2001). Street-based routing using an evolutionary algorithm. In E. J. W. Boers, J. Gottlieb, P. L. Lanzi, R. E. Smith, S. Cagnoni, E. Hart, …H. Tijink (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM, Proceedings (495-504). https://doi.org/10.1007/3-540-45365-2_51

Much research has been carried out into solving routing problems using both Evolutionary Techniques and other methods. In this paper the authors investigate the usage of an Evolutionary Algorithms to solve the Street-Based Routing Problem (SBRP). The... Read More about Street-based routing using an evolutionary algorithm.

Real-world applications of evolutionary computing (2000)
Conference Proceeding
Cagnoni, S., Poli, R., Smith, G. D., Corne, D., Oates, M., Hart, E., …Fogarty, T. C. (2000). Real-world applications of evolutionary computing. In Proceedings of EvoWorkshops 2000

This book constitutes the refereed proceedings of six workshops on evolutionary computation held concurrently as EvoWorkshops 2000 in Edinburgh, Scotland, UK, in April 2000. The 37 revised papers presented were carefully reviewed and selected by the... Read More about Real-world applications of evolutionary computing.

Solving CSPs with evolutionary algorithms using self-adaptive constraint weights. (2000)
Conference Proceeding
Eiben, A. E., Jansen, B., Michalewicz, Z., & Paechter, B. (2000). Solving CSPs with evolutionary algorithms using self-adaptive constraint weights. In D. Whitley (Ed.), GECCO-2000 : proceedings of the genetic and evolutionary computation conference (128-134)

This paper examines evolutionary algorithms (EAs) extended by various penalty-based approaches to solve constraint satisfaction problems (CSPs). In some approaches, the penalties are set in advance and they do not change during a run. In other appro... Read More about Solving CSPs with evolutionary algorithms using self-adaptive constraint weights..

Stone Soup (2000)
Conference Proceeding
Paechter, B., Fogarty, T. C., Burke, E., Cumming, A., & Rankin, B. (2000). Stone Soup. In Practice and Theory of Automated Timetabling III

Post-publication timetabling. (2000)
Conference Proceeding
Cumming, A., Paechter, B., & Rankin, R. C. (2000). Post-publication timetabling. In 3rd International Conference on the Practice And Theory of Automated Timetabling, PATAT 2000 (107-108)

Solving CSPs using self-adaptive constraint weights: how to prevent EAs from cheating (2000)
Conference Proceeding
Eiben, A. E., Jansen, B., Michalewicz, Z., & Paechter, B. (2000). Solving CSPs using self-adaptive constraint weights: how to prevent EAs from cheating. In GECCO'00: Proceedings of the 2nd Annual Conference on Genetic and Evolutionary Computation (128-134)

This paper examines evolutionary algorithms (EAs) extended by various penalty-based approaches to solve constraint satisfaction problems (CSPs). In some approaches, the penalties are set in advance and they do not change during a run. In other approa... Read More about Solving CSPs using self-adaptive constraint weights: how to prevent EAs from cheating.

Optimising an evolutionary algorithm for scheduling (2000)
Conference Proceeding
Urquhart, N. B., Chisholm, K., & Paechter, B. (2000). Optimising an evolutionary algorithm for scheduling. In S. Cagnoni, R. Poli, G. D. Smith, D. Corne, M. Oates, E. Hart, …T. C. Fogarty (Eds.), Real-World Applications of Evolutionary Computing: EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Proceedings (307-318). https://doi.org/10.1007/3-540-45561-2_30

This paper examines two techniques for setting the parameters of an evolutionary Algorithm (EA). The example EA used for test purposes undertakes a simple scheduling problem. An initial version of the EA was tested utilising a set of parameters that... Read More about Optimising an evolutionary algorithm for scheduling.

Two evolutionary approaches to cross-clustering problems. (1999)
Conference Proceeding
Luchian, H., Paechter, B., Radulescu, V., & Luchian, S. (1999). Two evolutionary approaches to cross-clustering problems. In Proceedings of the 1999 Congress on Evolutionary Computation (860-870). https://doi.org/10.1109/CEC.1999.782514

Cross-clustering asks for a Boolean matrix to be brought to a quasi-canonical form. The problem has many applications in image processing, circuit design, archaeology, ecology etc. The heuristics currently used to solve it rely on either topologi... Read More about Two evolutionary approaches to cross-clustering problems..

The continuous equilibrium optimal network design problem: a genetic approach. (1999)
Conference Proceeding
Cree, N. D., Maher, M., & Paechter, B. (1999). The continuous equilibrium optimal network design problem: a genetic approach. In M. G. H. Bell (Ed.), Transportation Networks: Recent Methodological advances (163-174)

A genetic algorithm (GA) program for providing a solution to the Continuous Equilibrium Network Design Problem (NDP) is introduced following a general discussion of the network design problem and genetic algorithms. A description of the current GA op... Read More about The continuous equilibrium optimal network design problem: a genetic approach..

Improving a lecture timetabling system for university wide use (1998)
Conference Proceeding
Paechter, B., Rankin, B., & Cumming, A. (1998). Improving a lecture timetabling system for university wide use. In Practice and Theory of Automated Timetabling II (156-165). https://doi.org/10.1007/BFb0055887

During the academic year 1996/97 the authors were commissioned by their institution to produce an automated timetabling system for use by all departments within the Faculty of Science. The system had to cater for the varying requirements of all the d... Read More about Improving a lecture timetabling system for university wide use.

Timetabling the classes of an entire university with an evolutionary algorithm. (1998)
Conference Proceeding
Paechter, B., Rankin, B., Cumming, A., & Fogarty, T. C. (1998). Timetabling the classes of an entire university with an evolutionary algorithm. In T. Beck, & M. Schoenauer (Eds.), Parallel Problem Solving from Nature - PPSN V (865-874). https://doi.org/10.1007/BFb0056928

This paper describes extensions to an evolutionary algorithm that timetables classes for an entire University. A new method of dealing with multi-objectives is described along with a user interface designed for it. New results are given concerning re... Read More about Timetabling the classes of an entire university with an evolutionary algorithm..

Extensions to a memetic timetabling system. (1996)
Conference Proceeding
Paechter, B., Cumming, A., Norman, M. G., & Luchian, H. (1996). Extensions to a memetic timetabling system. In R. Burke (Ed.), Practice and Theory of Automated Timetabling (251-265). https://doi.org/10.1007/3-540-61794-9_64

This paper describes work in progress to increase the performance of a memetic timetabling system. The features looked at are two directed mutation operators, targeted mutation and a structured population that facilitates parallel implementation. Exp... Read More about Extensions to a memetic timetabling system..

The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms. (1995)
Conference Proceeding
Paechter, B., Cumming, A., & Luchian, H. (1995). The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms. In Evolutionary Computing (86-93). https://doi.org/10.1007/3-540-60469-3_27

This paper presents a new genetic representation for timetabling with evolutionary algorithms. The representation involves the use of suggestion lists for the placement of events into timeslots. A set of recombination operators is defined for the new... Read More about The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms..

Optimising a Presentation Timetable Using Evolutionary Algorithms (1994)
Conference Proceeding
Paechter, B. (1994). Optimising a Presentation Timetable Using Evolutionary Algorithms. In Evolutionary Computing (264-276). https://doi.org/10.1007/3-540-58483-8_20

This paper describes a solution to the problem of scheduling student presentations which uses evolutionary algorithms. The solution uses a permutation based approach with each candidate schedule being coded for by a genotype containing six chromosome... Read More about Optimising a Presentation Timetable Using Evolutionary Algorithms.

Two solutions to the general timetable problem using evolutionary algorithms. (1994)
Conference Proceeding
Paechter, B., Luchian, H., Cumming, A., & Petriuc, M. (1994). Two solutions to the general timetable problem using evolutionary algorithms. In Proceedings of the IEEE World Congress in Computational Intelligence (300-305). https://doi.org/10.1109/ICEC.1994.349935

The general timetable problem, which involves the placing of events requiring limited resources into timeslots, has been approached in many different ways. This paper describes two approaches to solving the problem using evolutionary algorithms.... Read More about Two solutions to the general timetable problem using evolutionary algorithms..

A general model for the answer-pertubation techniques. (1994)
Conference Proceeding
Stamate, D., Luchian, H., & Paechter, B. (1994). A general model for the answer-pertubation techniques. In Proceedings of the 7th International Conference on Scientific and Statistical Database Management Systems (90-96). https://doi.org/10.1109/SSDM.1994.336958

Answer-perturbation techniques for the protection of statistical databases were introduced in [7]; they are flexible (perturbation kept under control), modular (do not interact with the DBMS) techniques, which compare fmorably to previous protec... Read More about A general model for the answer-pertubation techniques..

An evolutionary approach to the general timetable problem. (1993)
Book Chapter
Paechter, B., Luchian, H., & Cumming, A. (1993). An evolutionary approach to the general timetable problem. In The Scientific Annals of the "Al. I. Cuza" University of Iasi, special issue for the ROSYCS symposium 1993. Alexandru Ioan Cuza University Press