Work

An Integrated Model for Developing a Global Logistics Network Using Metaheuristic Algorithms

Year: 2025

Type: article

Abstract: The globalization of economies has heightened the importance of efficient logistics networks, particularly in the post-COVID-19 era where supply chain resilience is paramount. This study focuses on designing logistics hub networks to enhance global shipment flow management. A hub-based structure is adopted, aligned with existing global logistics frameworks. The research addresses key challenges such as optimizing warehouse and hub locations to streamline cargo delivery. An integrated model is developed for route planning, incorporating multi-modal transportation and cost-time trade-offs. The study employs metaheuristic algorithms including Strength Pareto Evolutionary Algorithm (SPEA-II), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and Multi-Objective Grey Wolf Optimization Algorithm to solve the proposed model. Detailed numerical analyses demonstrate the model's capability to generate optimal global solutions, underscoring its practical utility in real-world logistics management.

Source: Tehnicki vjesnik - Technical Gazette

DOI: 10.17559/tv-20240330001439

Authors: Mehrabadi, Reza Karimi, Roghanian, Emad, Piroozfar, Shahnaz, Shojaie, Abbas

Institutions: Islamic Azad University, Tehran, Islamic Azad University South Tehran Branch, K. N. Toosi University of Technology

Language: English

Topic: Facility Location and Emergency Management

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $431