Mixed-integer programming model and hybrid driving algorithm for multi-product partial disassembly line balancing problem with multi-robot workstations

To address the problem of considerable waste electromechanical product generation, a partial disassembly line balancing problem with multi-robot workstations that can synchronously disassemble multiple products (MPR-PDLBP) is investigated to improve the product capacity and efficiency of existing di...

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Vydané v:Robotics and computer-integrated manufacturing Ročník 73; s. 102251
Hlavní autori: Yin, Tao, Zhang, Zeqiang, Zhang, Yu, Wu, Tengfei, Liang, Wei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Elsevier Ltd 01.02.2022
Elsevier BV
Predmet:
Algorithms
Balancing
Cycle time
Dismantling
Energy consumption
Exact mixed-integer programming model
Hybrid driving algorithm
Integer programming
Mixed integer
Multi-product
Multi-robot workstation
Multiple robots
Optimization
Partial disassembly line
Solution space
Work stations
Workstations
Hybrid driving algorithm
Multi-robot workstation
Partial disassembly line
Exact mixed-integer programming model
Multi-product
ISSN:0736-5845, 1879-2537
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Shrnutí:To address the problem of considerable waste electromechanical product generation, a partial disassembly line balancing problem with multi-robot workstations that can synchronously disassemble multiple products (MPR-PDLBP) is investigated to improve the product capacity and efficiency of existing disassembly lines. First, an exact mixed-integer programming model is established to accurately obtain the minimum disassembly objectives: cycle time, energy consumption, and improved hazardous index. Second, compared with the conventional disassembly line balancing problem (DLBP), the solution space and optimization difficulty of MPR-PDLBP increase significantly. Thus, a multi-objective hybrid driving algorithm (HDA) based on a three-layer encoding method with a heuristic rule is proposed to effectively address MPR-PDLBP, and a driving strategy is proposed to improve the exploitation ability and convergence speed of HDA. Finally, validity of the proposed model and algorithm are verified by comparing the calculation results of GUROBI and HDA for two small-scale cases. The superiority of HDA is proved by comparing the optimization results of a large-scale case with three other classic algorithms.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0736-5845
1879-2537
DOI:10.1016/j.rcim.2021.102251