Journal Article10.1007/S001700170061
Optimal disassembly sequence using genetic algorithms considering economic and environmental aspects
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TL;DR: In this article, a GA-based approach for an optimal disassembly sequence considering economic and environmental aspects is presented, where all feasible disassembly sequences are generated by a disassembly tree or an AND/OR graph.
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Abstract: In this paper, a genetic algorithm (GA)-based approach for an optimal disassembly sequence considering economic and environmental aspects is presented. All feasible disassembly sequences are generated by a disassembly tree or an AND/OR graph. Using the disassembly precedence and the disassembly value matrix, a disassembly sequence is optimised. The precedence of disassembly is determined through a disassembly tree or an AND/OR graph and the value of disassembly is induced by considering both economic and environmental aspects in the disassembly, recycling, and disposal phases. Economic and environmental factors can be compared by the same measure through converting environmental factors into economic cost. To solve the disassembly sequence problem, a heuristic algorithm based on GAs is developed. The proposed GA can search for and dynamically explore the disassembly node through the highest disassembly value, keeping their precedence in order to identify an optimal disassembly sequence. It can also help to explore the search space, and an optimal solution can be obtained by applying the optimisation criteria. A refrigerator is used as an example to illustrate the procedure.
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Michael R. Johnson,M. H. Wang +1 more
TL;DR: In this article, the authors defined disassemblability of a product as the ability to optimize the design and disassembly process for removal of specific pans or materials in a manner which will minimize costs.
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Karim N. Taleb,Surendra M. Gupta +1 more
TL;DR: In this article, the problem of scheduling the disassembly of discrete parts products characterized by well-defined product structures is addressed, and two companion algorithms are presented to obtain a disassembling scheme for such problems.
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A.K. Subramani,P. Dewhurst +1 more
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