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Outputs (3)

Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation (2006)
Presentation / Conference Contribution
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 Artificia

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)
Presentation / Conference Contribution
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.