Outputs (101)

Variable neighbourhood search for job shop scheduling problems (2006)
Journal Article

Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for problem solving in which a systematic change of neighbourhood within a local search is carried out. In this paper, an investigation on implementing VNS for job shop... Read More about Variable neighbourhood search for job shop scheduling problems.

Parallel simulated annealing (2005)
Book Chapter

A simulated annealing algorithm for multi-agent systems: A job-shop scheduling application (2004)
Presentation / Conference Contribution

In this paper, a parallel implementation of the modular simulated annealing algorithm for classical job-shop scheduling is presented. The implementation is for a multi agent system running on the distributed resource machine, which is a novel, scalab... Read More about A simulated annealing algorithm for multi-agent systems: A job-shop scheduling application.

Parameterisation of mutation in evolutionary algorithms using the estimated main effect of genes (2004)
Presentation / Conference Contribution

This paper describes how to estimate the main effect of genes in genetic algorithms (GAs). The resulting estimates can not only be used to understand the domination of genes in a GA but also employed to tailor the mutation rate in the GA. A new appro... Read More about Parameterisation of mutation in evolutionary algorithms using the estimated main effect of genes.

An empirical study on the performance of factorial design based crossover on parametrical problems (2004)
Presentation / Conference Contribution

In the past, empirical studies have shown that factorial design based crossover can outperform standard crossover on parametrical problems. However, up to now, no conclusion has been reached as to what kind of landscape factorial design based crossov... Read More about An empirical study on the performance of factorial design based crossover on parametrical problems.

Teams of autonomous agents for job-shop scheduling problems: An experimental study (2004)
Presentation / Conference Contribution

ATeams - teams of autonomous agents co-operating by sharing solutions through a common memory-have been proposed as a means of solving combinatorial optimization problems. In this paper, the ATeam architecture is tested on the job-shop scheduling pro... Read More about Teams of autonomous agents for job-shop scheduling problems: An experimental study.

A Taguchi method-based crossover operator for the parametrical problems (2004)
Presentation / Conference Contribution

Based on our observation, some major steps in the genetic algorithm, such as the crossover operator, can be considered as experiments. The aim is to apply experimental design techniques to improve the crossover operator, so that the resulting operato... Read More about A Taguchi method-based crossover operator for the parametrical problems.

An epistasis measure based on the analysis of variance for the real-coded representation in genetic algorithms (2004)
Presentation / Conference Contribution

Epistasis is a measure of interdependence between genes and an indicator of problem difficulty in genetic algorithms. Many researches have concentrated on the epistasis measure in binary coded representation in genetic algorithms. However, a few atte... Read More about An epistasis measure based on the analysis of variance for the real-coded representation in genetic algorithms.

New factorial design theoretic crossover operator for parametrical problem (2003)
Presentation / Conference Contribution

Recent research shows that factorial design methods improve the performance of the crossover operator in evolutionary computation. However the methods employed so far ignore the effects of interaction between genes on fitness, i.e. "epistasis". Here... Read More about New factorial design theoretic crossover operator for parametrical problem.

Dynamic job-shop scheduling using reinforcement learning agents (2000)
Journal Article

Static and dynamic scheduling methods have attracted a lot of attention in recent years. Among these, dynamic scheduling techniques handle scheduling problems where the scheduler does not possess detailed information about the jobs, which may arrive... Read More about Dynamic job-shop scheduling using reinforcement learning agents.