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

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Intelligent Systems Design and Applications (ISDA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 736))

Abstract

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.

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Author information

Authors and Affiliations

  1. Institut Supérieur d’Informatique et des Techniques de Communication, University of Sousse, Rue G.P.1, 4011, Hammam Sousse, Tunisia

    Houda Harbaoui

  2. Institut Supérieur de Gestion de Sousse, University of Sousse, rue Abdlaaziz il Behi, BP763, 4000, Sousse, Tunisia

    Soulef Khalfallah

  3. Institut Mines Telecom Atlantique, LS2N, UMR CNRS 6004, 4 rue Alfred Kastler, La Chantrerie, BP20722, 44307, Nantes Cedex 3, France

    Houda Harbaoui & Odile Bellenguez-Morineau

Authors
  1. Houda Harbaoui
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  2. Soulef Khalfallah
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  3. Odile Bellenguez-Morineau
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Corresponding author

Correspondence to Houda Harbaoui .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs , Auburn, Washington, USA

    Ajith Abraham

  2. Department of Computer Science, South Asian University, Chanakyapuri, Delhi, India

    Pranab Kr. Muhuri

  3. Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka , Durian Tunggal, Melaka, Malaysia

    Azah Kamilah Muda

  4. Machine Intelligence Research Labs , Auburn, Washington, USA

    Niketa Gandhi

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Harbaoui, H., Khalfallah, S., Bellenguez-Morineau, O. (2018). A Novel Hybrid GA for the Assignment of Jobs to Machines in a Complex Hybrid Flow Shop Problem. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_62

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  • DOI: https://doi.org/10.1007/978-3-319-76348-4_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76347-7

  • Online ISBN: 978-3-319-76348-4

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