Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times

This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration o...

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Veröffentlicht in:	PloS one 2016-12, Vol.11 (12), p.e0167427-e0167427
Hauptverfasser:	Yang, Xin, Zeng, Zhenxiang, Wang, Ruidong, Sun, Xueshan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Biology and Life Sciences Classification Completion time Energy consumption Energy Metabolism Engineering Engineering and Technology Genetic algorithms Job shops Linear programming Manufacturing Manufacturing industry Mathematical models Methods Models, Theoretical Optimization Physical Sciences Problems Production scheduling Research and Analysis Methods Researchers Scheduling Small & medium sized enterprises-SME Sorting algorithms Stochastic Processes Stochasticity Studies
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