Optimizing the intermodal transportation of emergency medical supplies using balanced fuzzy clustering

In this paper, we are concerned with the problem of the ‘helicopters and vehicles’ intermodal transportation of medical supplies in response to large-scale disasters. To deal with the disadvantages of the use of classic Fuzzy C-Means (FCM) in the intermodal transportation optimization, two balanced FCM methods, i.e. FCM with capacity constraints and FCM with number constraints, are formulated to select emergency distribution centers (EDCs) and assign medical aid points, which could construct balanced ‘helicopters and vehicles’ intermodal transportation network. Then, considering helicopter travel time, transfer time and vehicle delivery time, a clustering-based intermodal routes optimization model is presented to produce intermodal transportation routes. Numerical experiments are presented to show the effectiveness and advantage of the developed approach, and observe the impact of number of EDCs and transfer efficiency at EDCs on the performance of intermodal transportation. This paper could provide methodological and operational supports for the ‘helicopters and vehicles’ intermodal transportation of medical supplies in response to large-scale disasters.