Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.
In: PLoS ONE, Jg. 11 (2016-12-01), Heft 12, S. 1-13
Online
academicJournal
Zugriff:
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 of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems. [ABSTRACT FROM AUTHOR]
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Titel: |
Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.
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Autor/in / Beteiligte Person: | Yang, Xin ; Zeng, Zhenxiang ; Wang, Ruidong ; Sun, Xueshan |
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Zeitschrift: | PLoS ONE, Jg. 11 (2016-12-01), Heft 12, S. 1-13 |
Veröffentlichung: | 2016 |
Medientyp: | academicJournal |
ISSN: | 1932-6203 (print) |
DOI: | 10.1371/journal.pone.0167427 |
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