A Bi-objective Evolutionary Algorithm to Improve the Service Quality for On-Demand Mobility

Abstract

This work aims at improving the quality of the service provided to the customers within real-life and customized demand-responsive transportation systems. Therefore, a new bi-objective model is designed to minimize both the total transit time which induces lower costs for the transportation service providers and the total waiting time for the travellers. To solve the new problem, an evolutionary algorithm is proposed based on two perturbation operators. A comparison between the proposed method and a hybrid evolutionary one from the literature is carried out. Preliminary computational experiments show the effectiveness of our method regardless of the complexity of the evolutionary schema operated. Some promising outputs are obtained allowing us to follow up the research for larger-scale transport-on-demand problems.