An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem

Authors:
Abdellah Salhi;José Antonio Vázquez Rodríguez;Qingfu Zhang
Affiliations:
University of Essex, Colchester, United Kingdom;Jubilee Campus: University of Nottingham, Nottingham, United Kingdom;University of Essex, Colchester, United Kingdom
Venue:
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Year:
2007

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Abstract

An Estimation of Distribution Algorithm (EDA) is proposed toapproach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similarproblems. Encouraging results are reported.