A hybrid single and dual population search procedure for the job shop scheduling problem

A hybrid single and dual population search procedure for the job shop scheduling problem

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Article ID: iaor20118849
Volume: 215
Issue: 3
Start Page Number: 512
End Page Number: 523
Publication Date: Dec 2011
Journal: European Journal of Operational Research
Authors: , ,
Keywords: heuristics: genetic algorithms
Abstract:

This paper presents a genetic algorithm and a scatter search procedure to solve the well‐known job shop scheduling problem. In contrast to the single population search performed by the genetic algorithm, the scatter search algorithm splits the population of solutions in a diverse and high‐quality set to exchange information between individuals in a controlled way. The extension from a single to a dual population, by taking problem specific characteristics into account, can be seen as a stimulator to add diversity in the search process. This has a positive influence on the important balance between intensification and diversification. Computational experiments verify the benefit of this diversity on the effectiveness of the meta‐heuristic search process. Various algorithmic parameters from literature are embedded in both procedures and a detailed comparison is made. A set of standard instances is used to compare the different approaches and the best obtained results are benchmarked against heuristic solutions found in literature.

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