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

An Estimation of Distribution Algorithm (EDA) is proposed to approach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFSSDST-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 similar problems. Encouraging results are reported. Categories and Subject Descriptors G.4 [Mathematical Software]: Algorithm design and analysis General Terms Algorithms Keywords Metaheuristics, combinatorial optimization, timetabling and scheduling

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Abdellah Salhi, José Antonio Vázquez Rodríguez, Qingfu Zhang
• Keywords: Algorithms Keywords Metaheuristics, GECCO 2007, Hybrid Flow Shop, Sequence Dependent Setup