Title :
A Hybrid CFGTSA Based Approach for Scheduling Problem: A Case Study of an Automobile Industry
Author :
Chan, Felix T S ; Kumar, Vikas ; Chan, H.K. ; Chung, S.H.
Author_Institution :
Hong Kong Univ., Kowloon
Abstract :
In the global competitive world swift, reliable and cost effective production subject to uncertain situations, through an appropriate management of the available resources, has turned out to be the necessity for surviving in the market. This inspired the development of the more efficient and robust methods to counteract the existing complexities prevailing in the market. The present paper proposes a hybrid CFGTSA algorithm inheriting the salient features of GA, TS, SA, and chaotic theory to solve the complex scheduling problems commonly faced by most of the manufacturing industries. The proposed CFGTSA algorithm has been tested on a scheduling problem of an automobile industry, and its efficacy has been shown by comparing the results with GA, SA, TS, GTS, and hybrid TSA algorithms.
Keywords :
automobile industry; chaos; genetic algorithms; scheduling; search problems; simulated annealing; automobile industry; chaotic theory; genetic algorithm; hybrid CFGTSA; hybrid chaos-based fast genetic tabu simulated annealing algorithm; manufacturing industries; scheduling problem; tabu search; Automobiles; Chaos; Costs; Job shop scheduling; Manufacturing industries; Production; Resource management; Robustness; Scheduling algorithm; Testing; CFGTSA; GA; SA; Scheduling; TS; chaotic theory;
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
DOI :
10.1109/ICSMC.2006.385107