Heuristics for a cash-collection routing problem with a cluster-first route-second approach

Abstract Motivated by a routing problem faced banks to enhance their encashment services in the city of Perm, Russia, we solve versions traveling salesman (TSP) with clustering. To minimize risk theft, suppliers seek operate multiple vehicles and determine an efficient routing; and, single vehicle serves set locations that forms cluster. This need form independent clusters—served distinct vehicles—allows use so-called cluster-first route-second approach. We are especially interested heuristics easily implementable understandable practitioners require only open-source solvers. this end, provide short survey 13 such for solving TSP, five clustering locations, three optimal number clusters—all using data from Perm. demonstrate practicality efficiency heuristics, further compare our heuristic solutions against tours. then statistical guarantees on quality solution. All anonymized code is publicly available allowing extensions practitioners, as decision-analytic framework both TSP.