Title :
Using genetic algorithms for supporting combinatorially complex decisions
Author_Institution :
Dept. of Comput. Inf. Syst., California State Univ., Turlock, CA, USA
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.635172
