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All Outputs (33)

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. (2002)
Presentation / Conference Contribution
Ross, P., Schulenburg, S., Marin-Blazquez, J. G., & Hart, E. (2002, July). Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. Presented at Genetic and Evolutionary Computation Conference (GECCO)

Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They can also take much longer than non-evolutionary methods. We
try to addres... Read More about Hyper-heuristics: learning to combine simple heuristics in bin-packing problems..

Improving street based routing using building block mutations. (2002)
Presentation / Conference Contribution
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002, April). Improving street based routing using building block mutations. Presented at Workshops on Applications of Evolutionary Computation EvoWorkshops 2002, Kinsale, Ireland

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..

GAVEL - a new tool for genetic algorithm visualization (2001)
Journal Article
Hart, E., & Ross, P. (2001). GAVEL - a new tool for genetic algorithm visualization. IEEE Transactions on Evolutionary Computation, 5(4), 335-348. https://doi.org/10.1109/4235.942528

This paper surveys the state of the art in evolutionary algorithm visualization and describes a new tool called GAVEL. It provides a means to examine in a genetic algorithm (GA) how crossover and mutation operations assembled the final result, where... Read More about GAVEL - a new tool for genetic algorithm visualization.

Clustering Moving Data with a Modified Immune Algorithm (2001)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2001, April). Clustering Moving Data with a Modified Immune Algorithm. Presented at Workshops on Applications of Evolutionary Computation EvoWorkshops 2001, Como, Italy

In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering have been proposed, none appear to specifically address the task of clustering... Read More about Clustering Moving Data with a Modified Immune Algorithm.

Enhancing the performance of a GA through visualisation. (2000)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2000, July). Enhancing the performance of a GA through visualisation. Presented at GECCO 2000

This article describes a new tool for visualising genetic algorithms, (GAs) which is designed in order to allow the implicit mechanisms
of the GA | i.e. crossover and mutation | to be thoroughly analysed. This allows the user to determine whether th... Read More about Enhancing the performance of a GA through visualisation..

An immune system approach to scheduling in changing environments. (1999)
Presentation / Conference Contribution
Hart, E., & Ross, P. (1999, July). An immune system approach to scheduling in changing environments. Presented at Genetic and Evolutionary Computation Conference ; GECCO-99

This paper describes the application of an artificial immune system, (AIS), model to a scheduling application, in which sudden changes in the scheduling environment require the rapid production of new schedules. The model operates in two phases: In t... Read More about An immune system approach to scheduling in changing environments..

Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem. (1999)
Journal Article
Hart, E., Ross, P., & Nelson, J. (1999). Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem. Annals of Operations Research, 92, 363-380. https://doi.org/10.1023/A%3A1018951218434

Genetic Algorithms (GAs) are a class of evolutionary algorithms that have been successfully
applied to scheduling problems, in particular job-shop and flow-shop type problems
where a number of theoretical benchmarks exist. This work applies a genet... Read More about Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem..

A heuristic combination method for solving job-shop scheduling problems. (1998)
Presentation / Conference Contribution
Hart, E., & Ross, P. (1998, September). A heuristic combination method for solving job-shop scheduling problems

This paper describes a heuristic combination based genetic algorithm, (GA), for tackling dynamic job-shop scheduling problems. Our approach is novel in that the genome encodes a choice of algorithm to be used to produce a set of schedulable operation... Read More about A heuristic combination method for solving job-shop scheduling problems..

Producing robust schedules via an artificial immune system. (1998)
Presentation / Conference Contribution
Hart, E., Ross, P., & Nelson, J. (1998, May). Producing robust schedules via an artificial immune system

This paper describes an artificial immune system (AIS) approach
to producing robust schedules for a dynamic jobshop
scheduling problem in which jobs arrive continually,
and the environment is subject to change due to practical
reasons. We investi... Read More about Producing robust schedules via an artificial immune system..

An adaptive mutation scheme for a penalty-based graph-colouring GA. (1998)
Presentation / Conference Contribution
Ross, P., & Hart, E. (1998, September). An adaptive mutation scheme for a penalty-based graph-colouring GA

The folklore of evolutionary algorithms still seems to contain some gross over-generalistions, such as that direct encodings are inferior to indirect ones, that penalty-function methods are often poor, and that observed performance on a few instances... Read More about An adaptive mutation scheme for a penalty-based graph-colouring GA..

Some observations about GA-based exam timetabling. (1998)
Presentation / Conference Contribution
Ross, P., Hart, E., & Corne, D. (1997, August). Some observations about GA-based exam timetabling. Presented at Second International Conference, PATAT’97, Toronto, Canada

Although many people have tried using genetic algorithms (GAs) for exam timetabling, far fewer have done systematic investigations to try to determine whether a GA is a good choice of method or not. We have extensively studied GAs that use one partic... Read More about Some observations about GA-based exam timetabling..

Solving a real-world problem using an evolving heuristically driven schedule builder. (1998)
Journal Article
Hart, E., Ross, P., & Nelson, J. (1998). Solving a real-world problem using an evolving heuristically driven schedule builder. Evolutionary Computation, 6(1), 61-80. https://doi.org/10.1162/evco.1998.6.1.61

This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be... Read More about Solving a real-world problem using an evolving heuristically driven schedule builder..