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A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem

Abstract : A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling n independent jobs on m identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific problem. Then, since this problem is NP hard in the strong sense, two well-known approximated methods, NSGA-II and SPEA-II, are adopted to solve it. Experimental results show the advantages of NSGA-II for the studied problem. An exact method is then applied to be compared with NSGA-II algorithm in order to prove the efficiency of the former. Experimental results show the advantages of NSGA-II for the studied problem. Computational experiments show that on all the tested instances, our NSGA-II algorithm was able to get the optimal solutions.
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https://hal-utt.archives-ouvertes.fr/hal-02478657
Contributor : Daniel Gavrysiak <>
Submitted on : Friday, February 14, 2020 - 9:08:02 AM
Last modification on : Saturday, February 15, 2020 - 1:36:24 AM

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Xiaohui Li, Lionel Amodeo, Farouk Yalaoui, Hicham Chehade. A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem. Advances in Artificial Intelligence, 2010, 2010, pp.1-10. ⟨10.1155/2010/943050⟩. ⟨hal-02478657⟩

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