AI Summary & Key Takeaways
AI InsightAccording to the results obtained from computational experiments, we show that taking into account both flow related costs and capacities of network components concurrently is very important to have a cost effective design.
📌 3 Key Takeaways
Abstract
The aim of the Capacitated Multiple Allocation Hub Covering Flow Problem is to find the optimal design for hub-and-spoke networks while taking into account hub opening and demand routing costs. Every network node has the potential to be a hub and demand from an origin to a destination must be sent through at least one hub. The network is incomplete in the sense that the maximum allowed or coverage distance between any opened hub and demand origin/ destination is predefined. It is assumed that there is a cost saving to route demand via hubs due to consolidation. Another important issue is the consideration of capacity restrictions imposed on network links and opened hubs. The problem is developed as a mixed-integer linear optimization problem. According to the results obtained from computational experiments, we show that taking into account both flow related costs and capacities of network components concurrently is very important to have a cost effective design.