Title: Multi-objective hierarchical model for coupled intelligent optimisation of master production planning and material management and its optimisation research

Authors: Yong Jin; Yanghua Gao; Fanghua Ning; Yutao Jin

Addresses: Information Center, China Tobacco Zhejiang Industrial Co., LTD., Hangzhou, 310002, Zhejiang, China ' Information Center, China Tobacco Zhejiang Industrial Co., LTD., Hangzhou, 310002, Zhejiang, China ' School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, Zhejiang, China ' School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, Zhejiang, China

Abstract: To address the insufficient integration between master production scheduling (MPS) and material management (MM) in China's tobacco industry, this study proposes a multi-objective hierarchical model for their collaborative optimisation. The model features a two-layer structure: the upper level optimises capacity utilisation and production costs, while the lower level minimises material waste and inventory levels. The NSGA-II algorithm was adopted to solve the model, and its effectiveness was verified through a case study based on actual enterprise operational data. Results demonstrate that the model significantly reduces raw-material waste by 19.3%, shortens the production cycle by 14 days, and improves Pareto-frontier efficiency by 32.7%. The study validates the model's effectiveness in complex, long-cycle production scenarios, offering a practical solution for refined production management in the tobacco industry.

Keywords: cigarette; master production planning; material management; multi-objective optimisation; genetic algorithm; progressive model.

DOI: 10.1504/IJCSM.2026.154298

International Journal of Computing Science and Mathematics, 2026 Vol.23 No.2, pp.103 - 122

Received: 23 Aug 2024
Accepted: 25 Sep 2025
Published online: 19 Jun 2026 *

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