Title: Genetic model for supply chain inventory optimisation

Authors: Mandeep Mittal; Charushi Nagpal; Nandini Malhotra; Annu Lambora; Reshu Agarwal; Sumil Mehta

Addresses: Department of Mathematics, Amity School of Engineering and Technology, New Delhi – 110061, India ' Department of Computer Science, Amity School of Engineering and Technology, New Delhi – 110061, India ' Department of Computer Science, Amity School of Engineering and Technology, New Delhi – 110061, India ' Department of Computer Science, Amity School of Engineering and Technology, New Delhi – 110061, India ' Department of Computer Science Engineering, G.L. Bajaj Institute of Technology and Management, Greater Noida-201310, India ' Department of Computer Science, Amity School of Engineering and Technology, New Delhi – 110061, India

Abstract: Inventory management is known to be an important aspect in supply chain models. The methodologies used in inventory optimisation intend to reduce the cost of supply chain by controlling the inventory in a desired manner, so that the members of supply chain will not be affected by abundance or shortage of stock. In this paper, an efficient approach based on genetic algorithm (GA) is proposed in order to reduce the total cost of supply chain. A numerical example is used to explain the new approach. The results show that the proposed approach gains an insight into the supply chain models and is applicable for reducing overall supply chain cost.

Keywords: supply chain; inventory management; genetic algorithm.

DOI: 10.1504/IJSCOR.2018.10014509

International Journal of Supply Chain and Operations Resilience, 2018 Vol.3 No.3, pp.248 - 259

Accepted: 14 Feb 2018
Published online: 24 Jul 2018 *

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