Solving vehicle routing problem with simultaneous pickup and delivery using parallel simulated annealing algorithm

Abstract

The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) is an NP-hard combinatorial optimisation problem that has received considerable attention in the past few decades. A parallel simulated annealing (parallel-SA) algorithm that uses four different neighbourhood structures has been developed to solve this problem. The parallel-SA algorithm follows the traditional sequential SA algorithm with an integrated asynchronous and synchronous multiple Markov chains (MMC) approach and incorporates a master-slave structure in the algorithm. Computational results are reported for 72 test problems with 50 to 400 customers from Dethloff's medium-scale benchmark, Salhi and Nagy's medium-to-large-scale benchmark and Montane and Galvao's large-scale benchmark. Computational results indicate that the proposed parallel-SA algorithm is competitive with other well-known algorithms for VRPSPD from both quality of solution and computational time.