Comparison of LSCP and Cluster Coverage Model for Emergency Train’s Assets Management:Use Case; North Eastern Railway

Abstract

Deployment of Accident Relief Medical Vans (ARMV) used for accident relief and rescue operations is generally done heuristically. ARMV is an ambulance-train equipped with various tools like jacks, heavy cutting tools, generators, operation theatre, artificial breathing equipment etc. to ease the rescue process. Taking North Eastern Railway (NER) as a case study, Location Set Covering Problem (LSCP) model will be used to find the minimum number of ARMVs required for the given network and their locations so that all demand points can be ‘covered’ within a maximum of one hour @ 100 kmph for each of the nearest facility. This paper proposes a new mathematical model based on the Cluster Coverage Model (CCM) to provide a better coverage of ARMV’s demands. We have used Girvan-Newman (GN) algorithm, a weight-based graph for clustering of NER network where nodes are taken as depots with ARMV parking facilities & crew availability and distance between these nodes is taken as edge weight of the graph. Finally, we present a comparison of results between the proposed cluster coverage models with LSCP and suggest relocations of the existing ARMVs and show that our proposed model is economical and provides a better coverage of ARMVs demands.