Title :
Research on the Production Scheduling for Automobile Parts Based on Hybrid Algorithm
Author :
Bing Li ; Wei Zhang ; Xingsheng Gu ; Lulu Cong
Author_Institution :
Sch. of Inf. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
The production of automobile parts is a job-shop scheduling problem, which is a NP-hard problem of the combinatorial optimization problems. Traditional algorithms for solving job-shop scheduling problems have their respective limitations. This paper proposes a hybrid algorithm to solve the problem of job-shop scheduling for automobile parts. It combines the advantage of global search ability of genetic algorithm with the strong local search ability of tabu search algorithm. The result of the simulation shows that this method is feasible and efficient.
Keywords :
automobile manufacture; combinatorial mathematics; genetic algorithms; job shop scheduling; search problems; NP-hard problem; automobile part production scheduling; combinatorial optimization problems; genetic algorithm; global search ability; hybrid algorithm; job-shop scheduling problem; local search ability; tabu search algorithm; Algorithm design and analysis; Automotive components; Genetic algorithms; Job shop scheduling; Sociology; Statistics; genetic algorithm; hybrid algorithm; job-shop scheduling; tabu search algorithm;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
DOI :
10.1109/IHMSC.2013.211