Energy-time tradeoffs for remanufacturing system scheduling using an invasive weed optimization algorithm

被引:34
|
作者
Wang, Wenjie [1 ,2 ]
Tian, Guangdong [1 ,2 ]
Yuan, Gang [3 ,4 ]
Pham, Duc Truong [5 ]
机构
[1] Shandong Univ, Natl Demonstrat Ctr Expt Mech Engn Educ, Sch Mech Engn,Minist Educ, Key Lab High Efficiency & Clean Mech Manufacture, Jinan 250061, Peoples R China
[2] Zhejiang Univ, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China
[3] Jilin Univ, Coll Biol & Agr Engn, Changchun 130022, Peoples R China
[4] Natl Univ Singapore, Dept Ind Syst Engn & Management, Singapore 119077, Singapore
[5] Univ Birmingham, Coll Mech Engn, Birmingham B15 2TT, W Midlands, England
基金
中国国家自然科学基金; 英国工程与自然科学研究理事会;
关键词
Remanufacturing system; Disassembly; Shop scheduling; Energy consumption; Multi-objective invasive weed optimization; DRUM-BUFFER-ROPE; MANUFACTURING SYSTEMS; TOTAL TARDINESS; SEQUENCE; DESIGN; MODEL; LIFE; SIMULATION; STRATEGIES; POLICIES;
D O I
10.1007/s10845-021-01837-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article studies the scheduling problem for a remanufacturing system with parallel disassembly workstations, parallel flow-shop-type reprocessing lines and parallel reassembly workstations. The problem is formulated as a multi-objective optimization problem which contains both energy consumption and makespan to be addressed using an improved multi-objective invasive weed optimization (MOIWO) algorithm. Two vectors regarding workstation assignment and operation scheduling jointly form a solution. A hybrid initialization strategy is utilized to improve the solution quality and the Sigma method is adopted to rate each solution. A novel seed spatial dispersal mechanism is introduced and four designed mutation operations cooperate to enhance search ability. A group of numerical experiments and a practical case involving the disassembly of transmission devices are carried out and the results validate the effectiveness of the MOIWO algorithm for the considered problem compared with existing methods.
引用
收藏
页码:1065 / 1083
页数:19
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