Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Job shop scheduling by simulated annealing
Operations Research
A tabu search experience in production scheduling
Annals of Operations Research - Special issue on Tabu search
Applying tabu search to the job-shop scheduling problem
Annals of Operations Research - Special issue on Tabu search
Tabu search for nonlinear and parametric optimization (with links to genetic algorithms)
Discrete Applied Mathematics - Special volume: viewpoints on optimization
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
On a scheduling problem in a robotized analytical system
Discrete Applied Mathematics - Special volume: first international colloquium on graphs and optimization (GOI), 1992
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Intelligent behavior as an adaptation to the task environment
Intelligent behavior as an adaptation to the task environment
An artificial bee colony algorithm for the unrelated parallel machines scheduling problem
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
An iterated greedy algorithm for the large-scale unrelated parallel machines scheduling problem
Computers and Operations Research
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We consider a robotized analytical system in which a chemicaltreatment has to be performed on a given set of identical samples. Theobjective is to carry out the chemical treatment on the wholeset of samples in the shortest possible time. All constraintshave to be satisfied since a modification of the chemicalprocess could create unexpected reactions.We have developed a new robust method governed by a geneticalgorithm to solve this scheduling problem. The crossovermechanism of this evolutionary method is based on an extensionof the uniform crossover introduced by Syswerda (1989).The proposed approach can be adapted to other combinatorialproblems where decisions, based on rules, have to be taken ateach step of a constructive method.