A Decision Support System for Solving Job-Shop Scheduling Problems using Genetic Al-gorithms

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Abstract
The primary objective of this research is to solve the job-shop scheduling problems by minimizing the makespan. In this paper, we first developed a genetic algorithm (GA) for solving JSSPs, and then improved the algorithm by integrating with three priority rules. The performance of the developed algorithm was tested by solving 40 benchmark problems and comparing their results with that of a number of well-known algorithms. For convenience of im-plementation, we developed a decision support system (DSS). In the DSS, we built a graphical user interface (GUI) for user friendly data inputs, model choices, and output generation. An overview of the DSS and the analysis of experimental results are provided.
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Author(s)
Hasan, S. M. Kamrul
Sarker, Ruhul
Essam, Daryl
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Publication Year
2008
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Conference Paper
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UNSW Faculty
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