Title :
An Improved Genetic Algorithm for Job Shop Scheduling Problem
Author :
Qing-dao-er-ji, Ren ; Wang, Yuping ; Si, Xiaojing
Author_Institution :
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an, China
Abstract :
Job shop scheduling problem is a typical NP-hard problem. In this paper, new designed crossover and mutation operators based on the characteristic of the job shop problem itself are specifically designed. Based on these, an improved genetic algorithm is proposed. The computer simulations are made on a set of benchmark problems and the results indicate the effectiveness of the proposed algorithm.
Keywords :
genetic algorithms; job shop scheduling; NP-hard problem; benchmark problems; crossover; genetic algorithm; job shop scheduling; mutation operators; Crossover oprator; Genetic algorithm; Job shop scheduling problem; Mutation operator;
Conference_Titel :
Computational Intelligence and Security (CIS), 2010 International Conference on
Conference_Location :
Nanning
Print_ISBN :
978-1-4244-9114-8
Electronic_ISBN :
978-0-7695-4297-3
DOI :
10.1109/CIS.2010.32
