We solve the disassembly-to-order (DTO) problem by using Evolutionary Computation. 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 products for the DTO system which satisfy the desirable criteria of the system. One of the most widely used forms of Evolutionary Computation is Genetic Algorithm (GA). GA, which has the capability to improve a set of solutions over evolutionary steps, is used to generate optimal number of take-back EOL products. Moreover, linear physical programming (LPP), which has key features to entirely remove the decision maker (DM) from the process of choosing weights and to handle the vagueness of aspiration levels, is used to calculate fitness values in the GA process. A numerical example is considered to illustrate the methodology.


Originally published in the Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing VI, Boston, Massachusetts, pp. 30-41, October 1-3, 2006


disassembly-to-order (DTO), end-of-life (EOL) products, Evolutionary Computation, Genetic Algorithm (GA), linear physical programming (LPP)

Subject Categories

Production engineering





Publication Date


Rights Information

Copyright 2006, Society of Photo-Optical Instrumentation Engineers


This paper was published in Proceedings of SPIE (Volume 6385) and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Rights Holder

Society of Photo-Optical Instrumentation Engineers

Click button above to open, or right-click to save.

Included in

Engineering Commons