title: Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.
abstract: 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.
authors.affiliation: School of Economics and Management, Hebei University of Technology, Tianjin, China.|ZhongHuan Information College Tianjin University of Technology, Tianjin, China.
authors.forename: Xin
authors.identifier: http://orcid.org/0000-0001-6636-9853
authors.initials: X
authors.lastname: Yang
authors.affiliation: School of Economics and Management, Hebei University of Technology, Tianjin, China.
authors.forename: Zhenxiang
authors.initials: Z
authors.lastname: Zeng
authors.affiliation: Department of Mathematics, Tianjin University of Technology, Tianjin, China.
authors.forename: Ruidong
authors.initials: R
authors.lastname: Wang
authors.affiliation: ZhongHuan Information College Tianjin University of Technology, Tianjin, China.
authors.forename: Xueshan
authors.initials: X
authors.lastname: Sun
mesh_terms: D000465:Algorithms; D004734:Energy Metabolism; D008962:Models, Theoretical; D013269:Stochastic Processes