Using genetic algorithms for supporting combinatorially complex decisions

Author

Deng, Pi-Sheng

Author_Institution

Dept. of Comput. Inf. Syst., California State Univ., Turlock, CA, USA

Volume

3

fYear

1997

fDate

12-15 Oct 1997

Firstpage

2086

Abstract

Combinatorially complex decisions are usually characterized by their huge size of solution space. For such type of decisions, optimal solutions are usually unattainable, and we can only approximate the optimal solutions. Due to their deterministicity, most of the traditional optimization techniques are limited by their power to discover satisfactory solutions for combinatorially complex decisions. In this paper, we designed a GA-based interactive system for the support of a combinatorially complex decision, namely the FMS batch selection problem. A performance analysis was conducted for different parameter settings for our system

Keywords

combinatorial mathematics; computer aided production planning; decision support systems; flexible manufacturing systems; genetic algorithms; interactive systems; FMS batch selection problem; GA-based interactive system; approximately optimal solutions; combinatorially complex decisions; genetic algorithms; performance analysis; Flexible manufacturing systems; Genetic algorithms; Information systems; Interactive systems; Job shop scheduling; Knowledge based systems; Performance analysis; Production planning; Stochastic processes; Switches;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.635172

Filename

635172