A combined model of network design and production/distribution planning for a supply network
Computers and Industrial Engineering - Supply chain management
Formulations and relaxations for a multi-echelon capacitated location-distribution problem
Computers and Operations Research
A Facility Location Model for Bidirectional Flows
Transportation Science
Hybrid genetic algorithm for multi-time period production/distribution planning
Computers and Industrial Engineering - Special issue: Selected papers from the 30th international conference on computers; industrial engineering
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path
Expert Systems with Applications: An International Journal
Close-loop or open hierarchical structures in green supply chain management under uncertainty
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Coordination among supply chains has elicited considerable attention in both academia and industry. This paper investigates an integrated supply chain network design problem that involves the determination of the locations for distribution centers and the assignment of customers and suppliers to the corresponding distribution centers. The problem simultaneously involves the distribution of products from the manufacturer to the customers and the collection of components from the suppliers to the manufacturer via cross-docking at distribution centers. The co-location of different types of distribution centers and coordinated transportation are introduced to achieve cost savings. A Lagrangian relaxation-based algorithm is then developed. Extensive computational experiments show that the proposed algorithm has stable performance and outperforms CPLEX for large-scale problems. An industrial case study is considered and sensitivity analysis is conducted to explore managerial insights. Finally, conclusions are drawn, and future research directions are outlined.