A genetic algorithm based heuristic for two machine no-wait flowshop scheduling problems with class setup times that minimizes maximum lateness

Machine scheduling problem has been extensively studied by researchers for many decades in view of its numerous applications on solving practical problems. Due to the complexity of this class of scheduling problems, various approximation solution approaches have been presented in the literature. In...

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Bibliographic Details
Published in:International journal of production economics 2013-01, Vol.141 (1), p.127-136
Main Author: Pang, King-Wah
Format: Article
Language:English
Subjects:
Approximation
Class based setup time
Economics
Effectiveness studies
Flowcharts
Genetic algorithm
Genetic algorithms
Heuristic
Job shops
Lateness
Mathematical analysis
Mathematical problems
Maximum lateness
No-wait flowshop
Production scheduling
Refineries
Scheduling
Setup times
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Summary:Machine scheduling problem has been extensively studied by researchers for many decades in view of its numerous applications on solving practical problems. Due to the complexity of this class of scheduling problems, various approximation solution approaches have been presented in the literature. In this paper, we present a genetic algorithm (GA) based heuristic approach to solve the problem of two machine no-wait flowshop scheduling problems that the setup time on the machines is class dependent, and the objective is to minimize the maximum lateness of the jobs processed. This class of machine scheduling problems has many practical applications in manufacturing industry, such as metal refinery operations, food processing industry and chemical products production processes, in which no interruption between subsequent processes is allowed and the products can be grouped into families. Extensive computation experiments have been conducted to evaluate the effectiveness of the proposed algorithm. Results show the proposed methodology is suitable to be adopted for the development of an efficient scheduling plan for this class of problems in real life application.
ISSN:0925-5273
1873-7579
DOI:10.1016/j.ijpe.2012.06.017