A Novel Hybrid GA for the Assignment of Jobs to Machines in a Complex Hybrid Flow Shop Problem

  • Houda Harbaoui
  • Soulef Khalfallah
  • Odile Bellenguez-Morineau
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)


This paper, investigates a complex manufacturing production system encountered in the food industry. We consider a two stage hybrid flow shop with two dedicated machines at stage1, and several identical parallel machines at stage 2. We consider two simultaneous constraints: the sequence dependent family setup times and time lags. The optimization criterion considered is the minimization of makespan. Given the complexity of problem, an hybrid genetic algorithms (HGA) based on an improving heuristic is presented. We experimented a new heuristic to assign jobs on the second stage. The proposed HGA is compared against a lower bound (LB), and against a mixed integer programming model (MIP). The results indicate that the proposed hybrid GA is effective and can produce near-optimal solutions in a reasonable amount of time.


Hybrid flow shop Sequence dependent family setup Hybrid genetic algorithm Time lag New heuristic Dedicated machine 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Houda Harbaoui
    • 1
    • 3
  • Soulef Khalfallah
    • 2
  • Odile Bellenguez-Morineau
    • 3
  1. 1.Institut Supérieur d’Informatique et des Techniques de CommunicationUniversity of SousseHammam SousseTunisia
  2. 2.Institut Supérieur de Gestion de SousseUniversity of SousseSousseTunisia
  3. 3.Institut Mines Telecom Atlantique, LS2N, UMR CNRS 6004Nantes Cedex 3France

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