Solving a disassembly-to-order system by using genetic algorithm and weighted fuzzy goal programming

Prasit Imtanavanich; Surendra M. Gupta

doi:10.1117/12.686263

9 October 2006 Solving a disassembly-to-order system by using genetic algorithm and weighted fuzzy goal programming

Proceedings Volume 6385, Environmentally Conscious Manufacturing VI; 638506 (2006) https://doi.org/10.1117/12.686263
Event: Optics East 2006, 2006, Boston, Massachusetts, United States

Abstract

In this paper, Genetic Algorithm (GA) is used to solve the disassembly-to-order (DTO) problem. DTO is a system where a variety of returned products are disassembled to fulfill the demand for specified numbers of components and materials. The main objective is to determine the optimal number of take-back EOL (end-of-life) products for the DTO system which satisfy the desirable criteria of the system. We implement the Weighted Fuzzy Goal Programming (WFGP) to calculate the fitness values in GA process. We also consider product deterioration which affects the yield rates (e.g., older products tend to have lower yield rates for usable components) and use heuristic procedure to transform the stochastic disassembly yields into their deterministic equivalents. A numerical example is also considered.

Citation Download Citation

Prasit Imtanavanich and Surendra M. Gupta "Solving a disassembly-to-order system by using genetic algorithm and weighted fuzzy goal programming", Proc. SPIE 6385, Environmentally Conscious Manufacturing VI, 638506 (9 October 2006); https://doi.org/10.1117/12.686263

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