The optimization of number of kanbans with genetic algorithms, simulated annealing and tabu search

Author

Alabas, Cigdem ; Altiparmak, Fulya ; Dengiz, Berna

Author_Institution

Dept. of Ind. Eng., Gazi Univ., Ankara, Turkey

Volume

1

fYear

2000

fDate

2000

Firstpage

580

Abstract

In this paper, three simulation search heuristic procedures, based on genetic algorithms, simulated annealing and tabu search, respectively, were developed and compared (both with respect to the best results achieved by each algorithm in a limited time span and to their speed of convergence) to the results for finding the optimum number of kanbans while minimizing the cost in a just-in-time manufacturing system

Keywords

convergence; genetic algorithms; heuristic programming; minimisation; production control; production engineering computing; search problems; simulated annealing; simulation; convergence speed; cost minimization; genetic algorithms; just-in-time manufacturing system; kanban number optimization; simulated annealing; simulation search heuristic procedures; tabu search; time span; Analytical models; Assembly systems; Control systems; Convergence; Design optimization; Genetic algorithms; Industrial engineering; Metamodeling; Simulated annealing; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2000. Proceedings of the 2000 Congress on

Conference_Location

La Jolla, CA

Print_ISBN

0-7803-6375-2

Type

conf

DOI

10.1109/CEC.2000.870349

Filename

870349