A hybrid genetic algorithm for the single machine maximum lateness problem with release times and family setups

A hybrid genetic algorithm for the single machine maximum lateness problem with release times and family setups

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Article ID: iaor20121528
Volume: 39
Issue: 10
Start Page Number: 2346
End Page Number: 2358
Publication Date: Oct 2012
Journal: Computers and Operations Research
Authors: ,
Keywords: heuristics: genetic algorithms, heuristics: local search
Abstract:

We consider the problem of scheduling a number of jobs, each job having a release time, a processing time, a due date and a family setup time, on a single machine with the objective of minimizing the maximum lateness. We develop a hybrid genetic algorithm and validate its performance on a newly developed diverse data set. We perform an extensive study of local search algorithms, based on the trade‐off between intensification and diversification strategies, taking the characteristics of the problem into account. We combine different local search neighborhood structures in an intelligent manner to further improve the solution quality. We use the hybrid genetic algorithm to perform a comprehensive analysis of the influence of the different problem parameters on the average maximum lateness value and the performance of the algorithm(s).

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