Journal of Industrial and Systems Engineering

Journal of Industrial and Systems Engineering

Fuzzy Multi-Objective Optimization Model for Online Businesses in International Markets: Reducing Response Time and Managing Inventory Uncertainty

Document Type : Research Paper

Authors
Anoosheh Chegini 1
Maryam Rahmaty 2
Mohammad Javad Taghipourian 3
Javad Gilanipour 1
1 Department of Management, Cha.C., Islamis Azad University, Chalous, Iran.
2 Department of Management, Chalous Branch, Islamic Azad University, Chalous, Iran.
3 Department of Management, Cha.C., Islamic Azad University, Chalus,Iran.
Abstract
International online businesses face several challenges in supply chain management, including reducing customer response time and managing uncertainty in inventory levels. This study proposes a fuzzy multi-objective optimization model to improve supply chain performance in international environments. This model uses fuzzy numbers to handle demand fluctuations, transportation costs, and delivery time, and provides a flexible decision-making framework. To solve this model, four meta-heuristic algorithms, including NSGA-II, PSO, GOA, and GA, are used, and their performance in terms of reducing supply chain costs, optimizing delivery time, and increasing inventory stability is investigated. The results show that PSO and GOA provide the shortest response time, while NSGA-II significantly reduces overall costs. Also, sensitivity analysis showed that NSGA-II and GOA are more stable regarding demand fluctuations, while GA has the least flexibility. This research presents a novel framework for supply chain optimization in international digital businesses that can help increase competitiveness and improve service levels in global markets.
Keywords
Supply chain optimization
metaheuristic algorithms
international e-commerce
fuzzy programming
response time
Subjects
Aliahmadi, A., Jafari-Eskandari, M., Mozafari, M., & Nozari, H. (2013). Comparing artificial neural networks and regression methods for predicting crude oil exports. International Journal of Information, Business and Management, 5(2), 40–58.
Ardolino, M., Bino, A., Ciano, M. P., & Bacchetti, A. (2025). Enabling digital capabilities with technologies: A multiple case study of manufacturing supply chains in disruptive times. Systems, 13(1), 39.
Balekelayi, N., Woldesellasse, H., & Tesfamariam, S. (2022). Comparison of the performance of a surrogate based Gaussian process, NSGA2 and PSO multi-objective optimization of the operation and fuzzy structural reliability of water distribution system. Water Resources Management, 36(15), 6169–6185.
Basar, G., & Der, O. (2025). Multi-objective optimization of process parameters using fuzzy AHP-based MCDM methods. Journal of Process Mechanical Engineering.
Fallah, M., & Nozari, H. (2021). Quantitative analysis of cyber risks in IoT-based supply chain. Journal of Decisions and Operations Research, 5(4), 510–521.
Ghahremani-Nahr, J., Nozari, H., & Bathaee, M. (2021). Robust box approach for supply chain network design under uncertainty. International Journal of Innovation in Engineering, 1(2), 40–62.
Goswami, S. S., et al. (2025). Artificial intelligence-enabled supply chain management. Artificial Intelligence and Applications, 3(1), 110–121.
Guo, J., Tang, B., Huo, Q., Liang, C., & Gen, M. (2021). Fuzzy programming of dual recycling channels. Arabian Journal for Science and Engineering, 46, 10231–10244.
Hashim, M., et al. (2017). Application of multi-objective optimization based on genetic algorithm. Journal of Industrial Engineering and Management, 10(2), 188–212.
Jiang, H., et al. (2018). A multi-objective PSO approach. Journal of Engineering Design, 29(7), 381–403.
Khan, A. J., & Das, D. K. (2014). Fuzzy multi objective optimization. Recent Research in Science and Technology, 6(1).
Rabiei, P., Arias-Aranda, D., & Stantchev, V. (2023). Multi-objective optimization with fuzzy systems. Expert Systems with Applications, 226, 120142.
Yammanur, V. (2025). Integrated enterprise systems for competitiveness. International Journal of Computer Engineering and Technology, 16, 454–466.
Zandvakili, A., Mansouri, N., & Javidi, M. M. (2021). Signature GOA. Journal of Algorithms and Computation, 53(1), 61–95.
Journal of Industrial and Systems Engineering
Volume 18, Issue 1
Winter 2026
Pages 83-104

  • Receive Date 29 October 2025
  • Revise Date 30 November 2025
  • Accept Date 06 December 2025