Title: Multi-objective optimisation of cigarette production planning and inventory management

Authors: Wanjiang Wang; Feng Zhao; Mingjun Wang; Qi Sun; Huihui Gao; Wei Jian; Renwang Li; Shulan Luo

Addresses: Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China ' Information Center, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou, Zhejiang, 100000, China

Abstract: This paper proposes a dynamic model-based optimisation method for cigarette production planning to meet market demand and optimise inventory management. The model contains three objectives: Minimising the difference between annual demand and production output, balancing monthly production and demand, and minimising the average age of inventory. The model sets annual demand constraints, production capacity constraints, and considers seasonal adjustment and contingency inventory. The model is solved by a combination of linear programming and genetic algorithms. The results show that the optimised production plan can effectively reduce total costs, avoiding the risks of under-supply and over-stocking. The analysis shows that the planned monthly production quantity closely matches the actual allocation quantity, the inventory management is effective, and hence the ability to cope with peak demand is enhanced.

Keywords: dynamic stocking model; cigarette production; linear programming; genetic algorithm; inventory management.

DOI: 10.1504/IJCSM.2025.146085

International Journal of Computing Science and Mathematics, 2025 Vol.21 No.1, pp.64 - 76

Received: 13 Oct 2024
Accepted: 12 Dec 2024
Published online: 06 May 2025 *

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