Title :
Apply Inversion Order Number Genetic Algorithm to the Job Shop Scheduling Problem
Author :
Yang, Xiaomei ; Zeng, Jianchao ; Liang, Jiye
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
Through analyzing the present genetic operators to solve the job shop scheduling problem, a inversion order number genetic algorithm is proposed. In view of the quality of the inversion order number, this algorithm measures the population diversity by the relative inversion order number. It uses the information provided by the inversion order number of the individual and the offspring is generated. This algorithm not only satisfies the characteristic of the job shop scheduling problem, but also develops the search capacity of genetic algorithm. The computation results validate the effectiveness of the proposed algorithm.
Keywords :
genetic algorithms; job shop scheduling; genetic algorithm; inversion order number; job shop scheduling problem; Algorithm design and analysis; Biological system modeling; Computer integrated manufacturing; Educational institutions; Genetic algorithms; Intelligent systems; Job design; Job shop scheduling; Laboratories; Scheduling algorithm; Genetic Algorithm; inversion order number; the Job Shop Scheduling Problem;
Conference_Titel :
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-0-7695-3899-0
DOI :
10.1109/WGEC.2009.104