DocumentCode :
3156920
Title :
Scheduling two-machine flow shop with a batch processing machine
Author :
Koh, Shiegheun ; Kim, Youngjin ; Lee, Woonseek
Author_Institution :
Dept of Syst. Manage. & Eng., Pukyong Nat. Univ., Busan, South Korea
fYear :
2009
fDate :
6-9 July 2009
Firstpage :
46
Lastpage :
51
Abstract :
This paper deals with the two-machine flow shop scheduling problem in which the first machine is a batch processing machine (BPM) that can process a number of jobs simultaneously, while the second machine is a discrete processing machine (DPM) that processes jobs one by one. To minimize makespan of the system, we present a mixed integer programming formulation for the problem. Using this formulation, we show that an optimal solution for small problem can be obtained by a commercial optimization software. However, since the problem is NP-hard and the size of real problems is usually large, we propose a number of heuristic algorithms including genetic algorithm to solve practical big-sized problems in a reasonable computational time. To verify the performances of the algorithms, we compare them with lower bound for the problem. From the results we obtained, some of the heuristic algorithms show very good performances.
Keywords :
batch processing (industrial); computational complexity; flow shop scheduling; genetic algorithms; integer programming; minimisation; NP-hard; batch processing machine; commercial optimization software; discrete processing machine; genetic algorithm; heuristic algorithms; makespan minimisation; mixed integer programming formulation; two-machine flow shop scheduling; Circuits; Engineering management; Genetic algorithms; Heuristic algorithms; Job shop scheduling; Linear programming; Ovens; Processor scheduling; Production; Systems engineering and theory; batch process; flow shop; heuristic; integer programming; scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers & Industrial Engineering, 2009. CIE 2009. International Conference on
Conference_Location :
Troyes
Print_ISBN :
978-1-4244-4135-8
Electronic_ISBN :
978-1-4244-4136-5
Type :
conf
DOI :
10.1109/ICCIE.2009.5223931
Filename :
5223931
Link To Document :
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