A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints

Routing and scheduling requests with pick-ups and deliveries is still one of the greatest operative challenges in inter-company logistics. Pick-up and delivery activities have to be bundled into efficient routes and their sequence has to be optimised within the routes without violating time and capacity constraints. The objective is to find a schedule of routes with minimal total costs. These costs result from the arising travelling costs, costs due to waiting and service times, and due to dispatching vehicles. This paper presents a guided local search method based on simulated annealing for solving this kind of routing and scheduling problem. Additionally, a new more realistic objective function that covers the total decision-relevant costs is introduced. The computational results show that the algorithm presented clearly outperforms standard implementations of simulated annealing and hill climber search.