مشخصات پژوهش

صفحه نخست /A hybrid multi-objective ...
عنوان A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem
نوع پژوهش مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها Scheduling, Flexible job shop, Multi-objective, genetic algorithm, ELECTREmethod, Pareto optimal front
چکیده In this paper, a multi-objective flexible job shop scheduling problem with machines capacity constraints is studied. Minimizing the makespan and overtime costs of machines are considered as two objectives for evaluating solutions. First, a new nonlinear integer programming model is presented to formulate the problem. Inasmuch as this problem is well-known as a NP-hard problem, a hybrid metaheuristic algorithm (CFJSP II) is developed to overcome its complexity. Regarding to the solution space of the problem, for assigning and sequencing operations, a multi-objective genetic algorithm based on the ELECTRE method is presented. Also, a powerful heuristic approach to tradeoff the objective functions is developed. Finally, the proposed algorithm is compared with some well-known multi-objective algorithms such as NSGAII, SPEA2, and VEGA. Regarding to the computational results, it is clear that the proposed algorithm has a better performance especially in the closeness of the solutions to the Pareto optimal front.
پژوهشگران محمد روحانی نژاد (نفر اول)، امیرسامان خیرخواه قه (نفر دوم)، پرویز فتاحی (نفر سوم)، بهدین واحدی نوری (نفر چهارم)