Stochastic Disassembly Sequence Optimization for Profit and Energy Consumption

Document Type

Conference Proceeding

Publication Date

7-2-2018

Abstract

Industrial products' reuse, recovery and recycling are very important because of their environmental and economic benefits. Effective disassembly sequencing can improve recovery revenue and reduce environment impact. In this work, a stochastic dual-objective disassembly sequencing problem is established, which includes maximizing disassembly profit and minimizing energy consumption. Two popular and classical multi-objective evolutionary algorithms, i.e., nondominated sorting genetic algorithm II and multi-objective evolutionary algorithm based on decomposition, are used to deal with this important problem. By conducting simulation experiments on several numerical cases and analyzing experimental results with two well-known performance metrics, i.e., inverted generational distance and hypervolume, this work concludes that both can be used to obtain highly desired solutions.

Identifier

85062209798 (Scopus)

ISBN

[9781538666500]

Publication Title

Proceedings 2018 IEEE International Conference on Systems Man and Cybernetics Smc 2018

External Full Text Location

https://doi.org/10.1109/SMC.2018.00246

First Page

1410

Last Page

1415

Grant

61703220

Fund Ref

National Natural Science Foundation of China

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