Title: Fuzzy genetic algorithm-based model for bullwhip effect reduction in a multi-stage supply chain

Authors: Marjia Haque; M. Ahsan Akhtar Hasin

Addresses: Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology (AUST), Dhaka-1208, Bangladesh ' Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh

Abstract: Synchronisation among supply chain (SC) stages is essential, but difficult to achieve, which results in a bullwhip effect. This paper proposes an interactive fuzzy-based genetic algorithm approach for reducing bullwhip effect by minimising total SC cost as well as to determine optimal ordering quantities in a multi-stage, multi-period SC using fuzzy logic combined with genetic algorithm. To face the uncertainty, forecasted customer demand and other SC cost related parameters are considered as uncertain parameters which are modelled through triangular fuzzy membership function. We used the strategy of simultaneously minimising the most possible value, the most pessimistic value and the most optimistic value of the total costs. Finally, a real-life case study is solved with the help of Matlab software to illustrate the usefulness of the approach where we employed different unique genetic algorithm parameters and compared the result obtained with existing policy and using only genetic algorithm.

Keywords: multi-stage supply chain; bullwhip effect; genetic algorithm; fuzzy logic; total supply chain cost.

DOI: 10.1504/IJSCIM.2021.114720

International Journal of Supply Chain and Inventory Management, 2021 Vol.4 No.1, pp.1 - 24

Accepted: 16 Jan 2020
Published online: 04 May 2021 *

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