Solving the pickup and delivery problem with time windows using reactive tabu search

The pickup and delivery problem with time windows requires that a group of vehicles satisfy a collection of customer requests. Each customer request requires the use of a single vehicle both to load a specified amount of goods at one location and to deliver them to another location. All requests must be performed without violating either the vehicle capacity or the customer time window stipulated at each location. In this paper, we present a reactive tabu search approach to solve the pickup and delivery problem with time windows using three distinct move neighborhoods that capitalize on the dominance of the precedence and coupling constraints. A hierarchical search methodology is used to dynamically alternate between neighborhoods in order to negotiate different regions of the solution space and adjust search trajectories. In order to validate our technique's effectiveness, we have constructed a new set of benchmark problems for the pickup and delivery problem with time windows based on Solomon's benchmark vehicle routing problem with time windows data sets. Computational results substantiate the solution quality and efficiency of our reactive tabu search approach.