Publication: Application of a genetic algorithm for multi-item inventory lot-sizing with supplier selection under quantity discount and lead time
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Issued Date
2020-01-01
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ISSN
17457653
17457645
17457645
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2-s2.0-85086044071
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Operational Research. Vol.38, No.3 (2020), 403-421
Suggested Citation
Sunan Klinmalee, Thanakorn Naenna, Chirawat Woarawichai Application of a genetic algorithm for multi-item inventory lot-sizing with supplier selection under quantity discount and lead time. International Journal of Operational Research. Vol.38, No.3 (2020), 403-421. doi:10.1504/IJOR.2020.107540 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/57846
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Title
Application of a genetic algorithm for multi-item inventory lot-sizing with supplier selection under quantity discount and lead time
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Abstract
Copyright © 2020 Inderscience Enterprises Ltd. This study presents an application of genetic algorithm (GA) for solving the multi-item inventory lot-sizing problem with supplier selection under discounts and lead time constraints. A mixed-integer linear programming (MILP) model is developed for proposed problem. To solve the problem, a genetic algorithm (GA) with two additional operations is proposed for handling the effect of the problem size. An adaptor for adjusting a chromosome data before the evaluation process and a penalty step for deterring an infeasible solution are developed. Finally, numerical examples are generated to evaluate the performance of the proposed GA, and the comparison with MILP approach about the solution quality and time is presented.