An Iterated Local Search for the Traveling Salesman Problem with Pickup, Delivery and Handling Costs

Abstract

In this paper the Traveling Salesman Problem with pickup, delivery and handling costs is studied. We have to find a route from a depot to a set of customers, each of which requires a pickup and delivery service. The goal is to minimize the global routing and handling cost. We have developed an Iterated Local Search for this problem combining different heuristics of the Traveling Salesman Problem, and using frequency of improvements and a perturbation with memory. The proposed algorithm is tested on different benchmark instances from the literature with up to 200 vertices, obtaining high quality solutions in reasonable computing times.