Supply Chain Optimization Footwear Products in West Java to Improve Industrial Competitiveness
DOI:
https://doi.org/10.37577/sainteks.v8i01.1077Keywords:
supply chain optimization, footwear industry, linear programming, EOQ, West Java, competitivenessAbstract
The footwear industry in West Java is one of the largest contributors to national manufacturing exports, yet it faces persistent challenges related to supply chain inefficiency, distribution costs, and competitive vulnerability. This study proposes a quantitative supply chain optimization framework for large-scale footwear manufacturers in West Java using Linear Programming (LP) and Economic Order Quantity (EOQ) models. The objective function minimizes total supply chain cost, encompassing procurement, transportation, and inventory holding costs, subject to supply capacity, demand fulfillment, and budget constraints. Primary data were collected from four major production centers—Bandung, Garut, Bogor, and Purwakarta—representing six supplier nodes and four distribution hubs. The LP model yields an optimal distribution plan that reduces total logistics cost by 18.4% compared to the existing plan, from Rp 4,320,000,000 to Rp 3,524,160,000 per year. EOQ analysis indicates an optimal order quantity of 15,625 pairs per order cycle, reducing inventory carrying cost by 22.7%. The results confirm that the proposed optimization approach significantly improves supply chain efficiency and enhances the competitiveness of West Java's footwear industry in both domestic and global markets
Downloads
References
Beheshtinia, M. A., Feizollahy, P., & Fathi, M. (2021). Supply chain optimization considering sustainability aspects. Sustainability (Switzerland), 13(21). https://doi.org/10.3390/su132111873
Bhagya, T. G. (2019). Penentuan Jumlah Pesanan Bahan Baku Pada Sistem Persediaan Backorder Di PT ABC. Sainteks - Universitas Bandung Raya, 1(2), 77–87. http://ejournal.uicm-unbar.ac.id/index.php/sainteks/article/view/128/52
BPS Jawa Barat. (2023). industrial-manufacturing-statistics-2022-of-jawa-barat-province.
Bridgelall, R. (2023). Tutorial and Practice in Linear Programming Optimization Problems in Supply Chain and Transport Logistics.
Fares, N., Lloret, J., Kumar, V., de Leeuw, S., & Barnes, L. (2024). Optimisation of multi-tier supply chain distribution networks with corporate social responsibility concerns in fast-fashion retail. Corporate Social Responsibility and Environmental Management, 31(1), 311–330. https://doi.org/10.1002/csr.2571
Li, J., Huang, H. Y., Lin, Y. C. D., Zuo, H., Tang, Y., & Huang, H. Da. (2023). Cinnamomi ramulus inhibits cancer cells growth by inducing G2/M arrest. Frontiers in Pharmacology, 14. https://doi.org/10.3389/fphar.2023.1121799
Lok, Y. W., Supadi, S. S., & Wong, K. Bin. (2022). EOQ Models for Imperfect Items under Time Varying Demand Rate. Processes, 10(6). https://doi.org/10.3390/pr10061220
Nugroho, I. S., Bhagya, T. G., & Rosinawati, D. (2020). Industri dan Supply Chain Halal Dilihat dari Aspek Keilmuan Teknik Industri. Jurnal Sains Dan Teknik, 2(2). http://ejournal.uicm-unbar.ac.id/index.php/sainteks/
Pujiastuti, L., Wahyudi, M., Jose Da Conceição, B., & Riandari, F. (2023). Journal of Intelligent Decision Support System (IDSS) Robust mathematical model for supply chain optimization: a comprehensive study. In Journal of Intelligent Decision Support System (IDSS) (Vol. 6, Number 2).
Riskadayanti, O., Hisjam, M., & Yuniaristanto, Y. (2020). Mixed-Integer Linear Programming Model for Production Planning: A Case Study at Sawn Timber Production. Jurnal Teknik Industri, 21(2), 163–173. https://doi.org/10.22219/jtiumm.vol21.no2.163-173
Vasilev, J., & Milkova, T. (2022). Optimisation Models for Inventory Management with Limited Number of Stock Items. Logistics, 6(3). https://doi.org/10.3390/logistics6030054
Vicente, J. J. (2025). Optimizing Supply Chain Inventory: A Mixed Integer Linear Programming Approach. Systems, 13(1). https://doi.org/10.3390/systems13010033
Wang, N., Chen, J., & Wang, H. (2023). Resilient Supply Chain Optimization Considering Alternative Supplier Selection and Temporary Distribution Center Location. Mathematics, 11(18). https://doi.org/10.3390/math11183955
Zhang, T., Xie, W., Wei, M., & Xie, X. (2023). Multi-objective sustainable supply chain network optimization based on chaotic particle—Ant colony algorithm. PLoS ONE, 18(7 July). https://doi.org/10.1371/journal.pone.0278814
