A Sample Average Approximation Approach for the Stochastic Dial-A-Ride Problem on a Multigraph with User Satisfaction

Abstract

In this study, we investigate a practical routing problem faced by a demand-responsive transportation service provider. To model the problem, we extend the dial-a-ride problem by defining the problem on a multigraph under a stochastic environment. The problem descriptions are provided first, and then we formulate the problem via a two-stage recourse model. To solve the problem, we design a sample average approximation procedure embedded with an adaptive large neighbourhood search algorithm. The proposed model and algorithm are then tested on instances generated from benchmarks and real-world data. The experiment results prove that the proposed algorithm can deal with the target problem properly, and considering stochastic factors and alternative paths in the underlying road network can reduce the operation cost and improve user satisfaction efficiently.