Simulated annealing approach for solving the fleet sizing problem in on-demand transit system

Abstract

Over the last years, operating expenses for on demand transit system have been increased as the demand for this type of transportation service has expanded. The on-demand transit system that we studied consists on moving a set of driverless electric taxi with bounded battery capacity. Many management algorithms have been proposed to improve the efficiency of such a system. In this paper, we propose to deal with the problem of determining the optimal fleet sizing of driverless electric taxis under a known transportation demand. We present a Simulated Annealing to solve the proposed problem. Evidence for the efficiency of our algorithm is proposed where computational results prove that our algorithm provide good quality solutions.