A parallel heuristic for the Vehicle Routing Problem with Simultaneous Pickup and Delivery

This paper presents a parallel approach for solving the Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD). The parallel algorithm is embedded with a multi-start heuristic which consists of a variable neighborhood descent procedure, with a random neighborhood ordering (RVND), integrated in an iterated local search (ILS) framework. The experiments were performed in a cluster with a multi-core architecture using up to 256 cores. The results obtained on the benchmark problems, available in the literature, show that the proposed algorithm not only improved several of the known solutions, but also presented a very satisfying scalability.