A Study on Optimal Location Selection and Semi-Finished Product Inventory Allocation in the Steel Industry

Zhiming Shi (), Yisong Li, Gábor Bohács and Qiang Zhou
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Zhiming Shi: School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
Yisong Li: School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
Gábor Bohács: Department of Material Handling and Logistic Systems, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
Qiang Zhou: School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China

Sustainability, 2022, vol. 14, issue 22, 1-21

Abstract: With the development of industrial production technologies and market economy, Postponement is increasingly being adopted by continuous production enterprise as a method that enables multi-product, mass customization production. In order to make use of the Postponement in manufacturing production enterprises need to achieve customized production and reduce enterprise costs. A modeling is conducted in the production process of Postponement in iron and steel enterprises in this paper. With the goal of minimizing total costs on a specific customer service level, mixed integer nonlinear programming and particle swarm algorithms are adopted for modeling and solving, to determine the optimal location and optimal semi-finished product inventory of PDP and CODP. Finally, taking an iron and steel enterprise as an example, the feasibility and effectiveness of the model and algorithm are verified. The study shows that the change of the optimal locations of PDP and CODP is affected by the change of customer service level and delay penalty coefficient, but the speed of change of the optimal location of PDP shows longer delays. In addition, the size of the capacity of semi-finished product inventory corresponding to CODP has a direct influence on whether the semi-finished product inventory corresponding to PDP participates in production, which in turn affects the optimal semi-finished product inventory on all levels. Through the analysis, it is found that the model constructed in this paper can better describe the overall situation and the influence relationship of the Postponement, and the study supplements the deficiency of the research on Postponement in the continuous manufacturing enterprises and enriches the content of the quantitative research on the Postponement.

Keywords: Postponement; iron and steel enterprises; PDP; CODP; particle swarm algorithms (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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