A Review of Combinatorial Optimization Problems in Reverse Logistics and Remanufacturing for End-of-Life Products

During the end-of-life (EOL) product recovery process, there are a series of combinatorial optimization problems (COPs) that should be efficiently solved. These COPs generally result from reverse logistics (RL) and remanufacturing, such as facility location and vehicle routing in RL, and scheduling,...

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Published inMathematics (Basel) Vol. 11; no. 2; p. 298
Main Authors Ren, Yaping, Lu, Xinyu, Guo, Hongfei, Xie, Zhaokang, Zhang, Haoyang, Zhang, Chaoyong
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2023
Subjects
combinational optimization
Combinatorial analysis
Consumers
End of life
Environmental impact
EOL product
Genetic algorithms
Linear programming
Manufacturers
Manufacturing
Mathematical models
Mathematics
Optimization
Product life cycle
Remanufacturing
Reverse logistics
Route planning
Scheduling
Supply chains
Vehicle routing
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Summary:During the end-of-life (EOL) product recovery process, there are a series of combinatorial optimization problems (COPs) that should be efficiently solved. These COPs generally result from reverse logistics (RL) and remanufacturing, such as facility location and vehicle routing in RL, and scheduling, planning, and line balancing in remanufacturing. Each of the COPs in RL and remanufacturing has been reviewed; however, no review comprehensively discusses and summarizes the COPs in both. To fill the gap, a comprehensive review of the COPs in both RL and remanufacturing is given in this paper, in which typical COPs arising at the end of the product life cycle are discussed and analyzed for the first time. To better summarize these COPs, 160 papers published since 1992 are selected and categorized into three modules: facility location and vehicle routing in RL, scheduling in remanufacturing, and disassembly in remanufacturing. Finally, the existing research gaps are identified and some possible directions are described.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11020298