An Improved Tabu Search Heuristic for Static Dial-A-Ride Problem
This work addresses efficient multi-vehicle routing for autonomous vehicle applications, but it is incremental as it builds on existing tabu search methods.
The paper tackled the static dial-a-ride problem by proposing an improved tabu search heuristic with new initialization and time window adjustment techniques, achieving faster convergence to high-quality solutions in short time, as validated through numerical experiments on standard test instances.
Multi-vehicle routing has become increasingly important with the rapid development of autonomous vehicle technology. Dial-a-ride problem, a variant of vehicle routing problem (VRP), deals with the allocation of customer requests to vehicles, scheduling the pick-up and drop-off times and the sequence of serving those requests by ensuring high customer satisfaction with minimized travel cost. In this paper, we propose an improved tabu search (ITS) heuristic for static dial-a-ride problem (DARP) with the objective of obtaining high-quality solutions in short time. Two new techniques, initialization heuristic, and time window adjustment are proposed to achieve faster convergence to the global optimum. Various numerical experiments are conducted for the proposed solution methodology using DARP test instances from the literature and the convergence speed up is validated.