Using chaos-parallel evolutionary programming to solve the flow-shop scheduling problem

Author

Xingwei, Liu ; Yongxiang, Pan ; Hongmei, Gao

Author_Institution

Xi´´an Univ. of Technol., China

Volume

3

fYear

2000

fDate

2000

Firstpage

2001

Abstract

In the paper, the chaos-parallel evolutionary programming algorithm is presented to solve the flow-shop scheduling problem. First, the individuals of each sub-population in the parallel evolutionary programming are found in the search space by use of the ergodicity properties of chaos states, then each sub-population evolves independently and the best individuals are exchanged between them periodically. Simulation results demonstrate that the new algorithm is efficient for optimizing large scale manufacturing process and the better results can be achieved on both the calculating time and optimizing rate

Keywords

chaos; evolutionary computation; production control; search problems; chaos-parallel evolutionary programming; ergodicity properties; flow-shop scheduling problem; large scale manufacturing process; search space; sub-population; Chaos; Genetic programming; Job shop scheduling; Large-scale systems; Manufacturing processes; Parallel programming; Scheduling algorithm; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.862919

Filename

862919