Title :
Job shop scheduling using Estimation of Distribution Algorithms
Author :
Fujimoto, Masahiro ; Eguchi, Toru
Author_Institution :
Grad. Sch. of Eng., Hiroshima Univ., Hiroshima, Japan
Abstract :
This paper presents an application of estimation of distributed algorithms to the job shop scheduling with the objective to minimize tardiness of jobs. The priority values for job selection are coded as genes and estimated by EDAs. Three kinds of methods for estimating the priorities are tested. In addition, the optimization method using the mixture of EDA and an effective priority rule for job selection is examined. Numerical experiments show that the performance of EDAs is comparable to that of a genetic algorithm using a random key coding.
Keywords :
genetic algorithms; job shop scheduling; random codes; EDA; distributed algorithms; distribution algorithm estimation; genetic algorithm; job selection; job shop scheduling; job tardiness; priority rule; random key coding; Biological cells; Decoding; Distributed algorithms; Electronic design automation and methodology; Genetic algorithms; Job shop scheduling; Optimization methods; Routing; Scheduling algorithm; Testing; Estimation of Distribution Algorithm; Genetic Algorithm; Job Shop Scheduling; Priority Rule;
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3
