Multi-objective pollution location-routing problem for improvement of a banking cash distribution network: A case study

One of the key processes in the banking system, is cash distribution from Treasury Branches and ATMs in the city. Treasury location, fleet, routes, geographical distribution of branches and ATMs, the distribution of money demand, customer satisfaction, are some of the influential factors in optimizing the money transfer process. Furthermore, today’s environmental issues, especially the issue of greenhouse gas (GHG) emissions, have been concentrated. In this paper, a new model of the location-routing vehicles for a bank cash distribution network is developed, in which three objectives of reducing GHG emissions, reducing costs of location-routing, and increasing customer satisfaction are considered simultaneously. Regarding to the difficulty of finding optimal solutions in such integrated models of location-routing problems, a multi-objective genetic algorithm-based on Prometheus methods are proposed. The obtained results are compared with the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective imperialist algorithm (MOICA). The comparison of these results shows the performance of the proposed algorithm for the given problems.