DocumentCode
1673565
Title
A Genetic Algorithm For Minimizing The Weighted Number Of Tardy Jobs
Author
Desprez, Caroline ; Chu, Chengbin ; Chu, Feng
Author_Institution
Inst. Charles Delaunay, Univ. de technologie de Troyes
Volume
2
fYear
2006
Firstpage
1271
Lastpage
1276
Abstract
This paper deals with a flow shop in which each operation needs several resources, some of these resources being polyvalent. The objective is to minimize the weighted number of tardy jobs. This problem represents a real industrial issue. The production system studied can be found in many companies. Currently, the firm that set the problem is using an industrial software. Our aim is to find a quick method to obtain better results than with this software. Because of the problem size and complexity, we decided to use a genetic algorithm to solve it. In this paper, we present this algorithm and we give some results obtained with it. Then we compare these results with those obtained with the software. These results show a clear improvement of the solution quality with the genetic algorithm
Keywords
computational complexity; flow shop scheduling; genetic algorithms; manufacturing systems; minimisation; flow shop scheduling; genetic algorithm; industrial software; production system; tardy job minimization; Aggregates; Computer industry; Genetic algorithms; Job shop scheduling; Manufacturing industries; Painting; Production systems; Resource management; Testing; Welding; Genetic Algorithm; multi-resource; re-entrant resources; weighted number of tardy jobs;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Systems and Service Management, 2006 International Conference on
Conference_Location
Troyes
Print_ISBN
1-4244-0450-9
Electronic_ISBN
1-4244-0451-7
Type
conf
DOI
10.1109/ICSSSM.2006.320691
Filename
4114673
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