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Application of a genetic algorithm for multi-item inventory lot-sizing with supplier selection under quantity discount and lead time

Author

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  • Sunan Klinmalee
  • Thanakorn Naenna
  • Chirawat Woarawichai

Abstract

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.

Suggested Citation

  • Sunan Klinmalee & Thanakorn Naenna & Chirawat Woarawichai, 2020. "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, Inderscience Enterprises Ltd, vol. 38(3), pages 403-421.
    • Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:403-421
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    Cited by:

    1. Sayan Chakraborty & Akshat Jain & S. P. Sarmah, 2022. "An integrated mathematical model based on grey optimal ranking for supplier selection considering pandemic situation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1613-1648, December.

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