Hub location with the backup approach by considering capacity constraint in critical situations

Document Type : Research Note

Authors

1 Isfahan Univ. of Tech.

2 Faculty member. Department of Industrial and Systems Engineering. Isfahan University of Technology

10.24200/j65.2024.62721.2365

Abstract

The efficient transportation of goods and passengers from origin to destination is a crucial aspect of supply chain management. The design of transportation systems plays a key role in determining system costs and customer satisfaction. In cases where direct communication between all points is not feasible, the hub and spoke system can be utilized. The design of the hub network is a strategic decision that faces uncertainties such as demand, costs, and system reliability. Natural and unnatural events can impact the efficiency of hub facilities, leading to additional costs for the system. Capacity limitations in hub facilities may necessitate crisis management strategies, such as transferring flows to backup hubs during emergencies. This study explores the use of single backup and multiple backup approaches to address hub unavailability and meet demand requirements. A mathematical model is presented to investigate and solve the single and multiple backup strategies. Due to the complexity of the problem, a genetic algorithm approach is employed for optimization. The performance of the algorithms is evaluated using the CAB dataset, demonstrating the effectiveness of the proposed solutions. Comparing the results of single backup and multiple backup strategies reveals that the latter is more advantageous in terms of system costs and congestion in hub nodes. This study highlights the importance of strategic planning in transportation systems and the benefits of implementing backup solutions to ensure efficient operations. This research underscores the critical role that transportation systems play in the overall success of supply chains and the significant impact that effective logistics management can have on customer satisfaction and operational costs. The strategic decisions made in designing transportation networks can have far-reaching implications on the overall efficiency and reliability of the system. By exploring different backup strategies and utilizing mathematical model organizations can better prepare for disruptions and ensure continuity of operations. The use of genetic algorithms and data analysis tools can provide valuable insights into the performance of transportation systems and help identify opportunities for improvement. Overall, this study emphasizes the importance of proactive planning and the adoption of innovative solutions in the field of logistics and transportation management.

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