Multi-restart iterative search for the pickup and delivery traveling salesman problem with FIFO loading

Abstract

The pickup and delivery traveling salesman problem with FIFO loading (TSPPDF) is a variant of the classic traveling salesman problem with pickup and delivery arising from several practical applications where services have to be carried out in the first-in-first-out fashion. In this paper, we present a multi-restart iterative search approach (MIS) for TSPPDF based on a combined use of 6 move operators. The basic idea behind MIS is to alternate between a threshold-based exploration phase, during which degrading solutions are considered as long as they satisfy a quality threshold, and a descent-based improvement phase that only accepts solutions that improve on the quality of the current solution. A dedicated restart strategy is applied to generate a new starting point for the next round of the iterative search as soon as the search is deemed trapped into a deep local optimum. Extensive experiments on a set of 42 benchmark instances from the literature show that the proposed approach competes very favorably with the existing methods from the literature. In particular, it reports new upper bounds (improved best-known solutions) for 20 instances, while matching the best-known result for the remaining instances. The key components of MIS are analyzed to shed light on their impact to the overall algorithmic performance.