Bi-Objective Modeling and Optimization for Stochastic Two-Stage Open Shop Scheduling Problems in the Sharing Economy

被引:33
作者
Fu, Yaping [1 ,2 ]
Li, Haobin [3 ]
Huang, Min [4 ]
Xiao, Hui [5 ]
机构
[1] Qingdao Univ, Sch Business, Qingdao 266071, Peoples R China
[2] Natl Univ Singapore, Dept Ind & Syst Engn, Singapore 117578, Singapore
[3] Natl Univ Singapore, Dept Ind Syst Engn & Management, Singapore 117578, Singapore
[4] Northeastern Univ, Coll Informat Sci & Engn, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
[5] Southwestern Univ Finance & Econ, Sch Stat, Chengdu 611130, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Optimization; Job shop scheduling; Maintenance engineering; Task analysis; Stochastic processes; Companies; Indexes; Discrete event system; migrating birds optimization (MBO); multiobjective optimization; sharing economy; two-stage open shop scheduling; MIGRATING BIRDS OPTIMIZATION; DEPENDENT SETUP TIMES; FLOW-SHOP; MULTIOBJECTIVE OPTIMIZATION; GENETIC ALGORITHM; PROGRAMMING-MODEL; MAINTENANCE; TECHNOLOGY; ASSIGNMENT; ALLOCATION;
D O I
10.1109/TEM.2021.3095954
中图分类号
F [经济];
学科分类号
02 ;
摘要
Nowadays, many manufacturing and service industries prefer to share resources such as facilities and workers to cooperatively perform tasks, which can efficiently improve resource utilization and customer satisfaction. Generally, the decision-makers need to pay more for resource usage, leading to an urgent demand to decrease operational costs. This article proposes a stochastic bi-objective two-stage open shop scheduling problem that models a vehicle maintenance process where tasks are appointed to be completed by multiple third-party companies with professional equipment. We formulate this optimization problem by minimizing the total tardiness and processing cost subject to various resource constraints. A hybrid multiobjective migrating birds optimization combined with a genetic operation and a discrete event system is designed by considering problem characteristics to solve the problem. In this method, the migrating birds optimization with some particular strategies aims at searching candidate solutions from the entire solution domain. Simultaneously, the discrete event system, by using stochastic simulation and discrete event-based simulation approaches, focuses on evaluating the performance of searched solutions. Simulation experiments are performed, and state-of-the-art algorithms are used as competitive approaches. The results confirm that this approach has an excellent performance in handling our considered problem.
引用
收藏
页码:3395 / 3409
页数:15
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