Scheduling and planning problem in manufacturing systems with multiobjective genetic algorithm

Author

Li, Y. ; Man, K.F.

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, Hong Kong

Volume

1

fYear

1998

fDate

31 Aug-4 Sep 1998

Firstpage

274

Abstract

In this paper an extensive earliness/tardiness production scheduling and planning (ETPSP) model with lot-size consideration and capacity balance is proposed. An innovative approach using a multiobjective genetic algorithm (MOGA) is designed as its solutions. The presented MOGA approach can even deal with ETPSP problem which consists of highly complicated and nonlinear functions for the measure performance. The effectiveness of this approach is demonstrated by simulation results as well as the comparisons with other techniques

Keywords

genetic algorithms; manufacturing industries; manufacturing resources planning; nonlinear functions; production control; scheduling; MRP-II; capacity balance; extensive earliness/tardiness production scheduling; just-in-time; lot-size consideration; manufacturing resource planning; manufacturing systems planning; manufacturing systems scheduling; multiobjective genetic algorithm; multiobjective optimisation; nonlinear functions; simulation; Algorithm design and analysis; Capacity planning; Electronic mail; Genetic algorithms; Inventory management; Job shop scheduling; Large-scale systems; Manufacturing systems; Materials requirements planning; Production planning;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE

Conference_Location

Aachen

Print_ISBN

0-7803-4503-7

Type

conf

DOI

10.1109/IECON.1998.724135

Filename

724135