Minimizing the energy consumption and the total weighted tardiness for the flexible flow shop using NSGA-II and NRGA
محل انتشار: چهاردهمین کنفرانس بین المللی مهندسی صنایع
سال انتشار: 1396
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 678
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شناسه ملی سند علمی:
IIEC14_076
تاریخ نمایه سازی: 26 مرداد 1397
چکیده مقاله:
This paper presents a bi-objective MIP model for the flexible flow shop scheduling problem (FFSP) in which the total weighted tardiness and the energy consumption are minimized simultaneously. In addition to considering unrelated machines at each stage, the set-up times are supposed to be sequence- and machine-dependent, and it is assumed that jobs have different release times. Two Taguchi-based-tuned algorithms: (i) non-dominated sorting genetic algorithm II (NSGA-II), and (ii) non-dominated ranked genetic algorithm (NRGA) are applied to solve the model. Six numerical examples with different sizes (small, medium, and large) are used to demonstrate the applicability and to exhibit the efficacy of the algorithms. The results show that the NRGA outperforms significantly the NSGA-II in the performance metrics for all six numerical examples.
کلیدواژه ها:
Flexible flow shop scheduling ، energy consumption ، weighted tardiness ، genetic algorithm ، strength Pareto evolutionary algorithm
نویسندگان
Mohammad Mahdi Nasiri
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Mojtaba Abdollahi
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Ali Rahbari
Department of Industrial Engineering, Alborz Campus, University of Tehran, Tehran, Iran
Navid Salmanzadeh Meydani
Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran