Evolutionary computation with linear physical programming for solving a disassembly-to-order system

Prasit Imtanavanich; Surendra M. Gupta

doi:10.1117/12.686269

9 October 2006 Evolutionary computation with linear physical programming for solving a disassembly-to-order system

Proceedings Volume 6385, Environmentally Conscious Manufacturing VI; 638504 (2006) https://doi.org/10.1117/12.686269
Event: Optics East 2006, 2006, Boston, Massachusetts, United States

Abstract

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.

Citation Download Citation

Prasit Imtanavanich and Surendra M. Gupta "Evolutionary computation with linear physical programming for solving a disassembly-to-order system", Proc. SPIE 6385, Environmentally Conscious Manufacturing VI, 638504 (9 October 2006); https://doi.org/10.1117/12.686269

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available