A Multi Objective Evolutionary Algorithm based on Decomposition for a Flow Shop Scheduling Problem in the Context of Industry 4.0

被引：7

作者：

Rossit, Diego Gabriel ^{[1
,2
,3
]}

Nesmachnow, Sergio ^{[4
]}

Rossit, Daniel Alejandro ^{[1
,2
,3
]}

机构：

[1] Univ Nacl Sur, Dept Engn, Bahia Blanca, Buenos Aires, Argentina

[2] Univ Nacl Sur, INMABB, Bahia Blanca, Buenos Aires, Argentina

[3] Consejo Nacl Invest Cient & Tecn, Bahia Blanca, Buenos Aires, Argentina

[4] Univ Republica, Montevideo, Uruguay

来源：

INTERNATIONAL JOURNAL OF MATHEMATICAL ENGINEERING AND MANAGEMENT SCIENCES | 2022年 / 7卷 / 04期

关键词：

Industry; 4.0; Flow shop; Missing operation; Evolutionary algorithms; Multi objective optimization; Makespan; Total tardiness; NON-PERMUTATION SCHEDULES; MANUFACTURING SYSTEMS; PERFORMANCE; MOEA/D; RULES;

D O I：

10.33889/IJMEMS.2022.7.4.029

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Under the novel paradigm of Industry 4.0, missing operations have arisen as a result of the increasingly customization of the industrial products in which customers have an extended control over the characteristics of the final products. As a result, this has completely modified the scheduling and planning management of jobs in modern factories. As a contribution in this area, this article presents a multi objective evolutionary approach based on decomposition for efficiently addressing the multi objective flow shop problem with missing operations, a relevant problem in modern industry. Tests performed over a representative set of instances show the competitiveness of the proposed approach when compared with other baseline metaheuristics.

引用

页码：433 / 454

页数：22

共 50 条

[31] A MULTI-OBJECTIVE HYBRID DIFFERENTIAL OPTIMIZATION ALGORITHM FOR FLOW-SHOP SCHEDULING PROBLEM
Pei, J. Y.
Shan, P.
INTERNATIONAL JOURNAL OF SIMULATION MODELLING, 2019, 18 (03) : 500 - 509
[32] Multi-Objective Evolutionary Algorithm Based on Decomposition for Air Traffic Flow Network Rerouting Problem
Zhang, Xiao
Xiao, Mingming
Zhang, Miao
INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2013, 2013, 8206 : 487 - 496
[33] A hybrid algorithm for multi-objective job shop scheduling problem
Li, Junqing
Pan, Quanke
Xie, Shengxian
Gao, Kaizhou
Wang, Yuting
2011 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, 2011, : 3630 - 3634
[34] Quantum Evolutionary Algorithm for Chemical Parallel Flow Shop Scheduling Problem
Tang, Qi
Liu, Peng
Tang, Jianxun
Li, Xiang
PROCEEDINGS OF THE AASRI INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (IEA 2015), 2015, 2 : 324 - 327
[35] An efficient evolutionary algorithm for multi-objective stochastic job shop scheduling
Lei, De-Ming
Xiong, He-Jin
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 867 - 872
[36] A multi-objective particle swarm for a flow shop scheduling problem
Rahimi-Vahed, A. R.
Mirghorbani, S. M.
JOURNAL OF COMBINATORIAL OPTIMIZATION, 2007, 13 (01) : 79 - 102
[37] Decomposition multi-objective evolutionary algorithm based photolithography area scheduling method
Zhang P.
Zhang J.
Wang Z.
Sun K.
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2022, 50 (04): : 26 - 32
[38] A matheuristic-based multi-objective evolutionary algorithm for flexible assembly jobs shop scheduling problem in cellular manufacture
Hu, Yifan
Zhang, Liping
Wang, Qiong
Zhang, Zikai
Tang, Qiuhua
SWARM AND EVOLUTIONARY COMPUTATION, 2024, 87
[39] A multi-objective particle swarm for a flow shop scheduling problem
A. R. Rahimi-Vahed
S. M. Mirghorbani
Journal of Combinatorial Optimization, 2007, 13 : 79 - 102
[40] A Pareto block-based estimation and distribution algorithm for multi-objective permutation flow shop scheduling problem
Tiwari, Anurag
Chang, Pei-Chann
Tiwari, M. K.
Kollanoor, Nevin John
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2015, 53 (03) : 793 - 834

← 1 2 3 4 5 →