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  • Open Access


    An Improved Hyperplane Assisted Multiobjective Optimization for Distributed Hybrid Flow Shop Scheduling Problem in Glass Manufacturing Systems

    Yadian Geng1, Junqing Li1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 241-266, 2023, DOI:10.32604/cmes.2022.020307

    Abstract To solve the distributed hybrid flow shop scheduling problem (DHFS) in raw glass manufacturing systems, we investigated an improved hyperplane assisted evolutionary algorithm (IhpaEA). Two objectives are simultaneously considered, namely, the maximum completion time and the total energy consumptions. Firstly, each solution is encoded by a three-dimensional vector, i.e., factory assignment, scheduling, and machine assignment. Subsequently, an efficient initialization strategy embeds two heuristics are developed, which can increase the diversity of the population. Then, to improve the global search abilities, a Pareto-based crossover operator is designed to take more advantage of non-dominated solutions. Furthermore, a local search heuristic based on… More >

  • Open Access


    Hybrid Flow Shop with Setup Times Scheduling Problem

    Mahdi Jemmali1,2,3,*, Lotfi Hidri4

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 563-577, 2023, DOI:10.32604/csse.2023.022716

    Abstract The two-stage hybrid flow shop problem under setup times is addressed in this paper. This problem is NP-Hard. on the other hand, the studied problem is modeling different real-life applications especially in manufacturing and high performance-computing. Tackling this kind of problem requires the development of adapted algorithms. In this context, a metaheuristic using the genetic algorithm and three heuristics are proposed in this paper. These approximate solutions are using the optimal solution of the parallel machines under release and delivery times. Indeed, these solutions are iterative procedures focusing each time on a particular stage where a parallel machines problem is… More >

  • Open Access


    An Efficient Hybrid Algorithm for a Bi-objectives Hybrid Flow Shop Scheduling

    S. M. Mousavia, M. Zandiehb

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 9-16, 2018, DOI:10.1080/10798587.2016.1261956

    Abstract This paper considers the problem of scheduling n independent jobs in g-stage hybrid flow shop environment. To address the realistic assumptions of the proposed problem, two additional traits were added to the scheduling problem. These include setup times, and the consideration of maximum completion time together with total tardiness as objective function. The problem is to determine a schedule that minimizes a convex combination of objectives. A procedure based on hybrid the simulated annealing; genetic algorithm and local search so-called HSA-GA-LS are proposed to handle this problem approximately. The performance of the proposed algorithm is compared with a genetic algorithm… More >

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