A Hyperheuristic Approach to Multi-Echelon Hub and Routing Optimization: Model, Valid Inequalities, and Case Study - Kassem Danach; Hassan Harb; Badih Baz; Abbass Nasser (IEEE Open Journal of Intelligent Transportation Systems, 2025)
Efficient logistics management is critical in the modern global supply chain, and this study introduces an advanced hyperheuristic approach to the Multi-Echelon Hub and Routing Optimization (MEHRO) problem. The MEHRO problem encompasses optimizing hub locations and vehicle routes while balancing cost efficiency, service quality, and environmental sustainability. A novel mathematical model integrates transportation, hub setup, and inventory costs, strengthened by valid inequalities to enhance computational efficiency. The hyperheuristic framework dynamically selects from a pool of low-level heuristics, adapting strategies to varying problem instances. A real-world case study validates the model’s effectiveness, demonstrating significant cost reductions, improved service levels, and minimized environmental impact compared to traditional methods. This work sets a foundation for scalable and adaptive solutions in logistics and combinatorial optimization, catering to the evolving demands of global supply chain management.