Title :
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
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;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870349
