A Particle Swarm Optimization for Selective Pickup and Delivery Problem

Abstract

This paper studies a variant of vehicle routing problem called Selective Pickup and Delivery Problem with Time Windows and Paired Demands (SPDPTWPD). A visiting sequence of each assigned vehicle needs to be determined by respecting the imposed constraints. Like for other combinatorial problems, the optimal solution cannot be obtained in a reasonable time when the size increases. An approached method is thus chosen as an alternative to tackle this issue. The proposed method integrates particle swarm optimization (PSO) with local searches by considering the diversification of PSO and intensification of local search. To validate the method, experiments are made on the benchmarks from the literature. The experiments are divided into two parts. In the first part, a self-comparison is made to demonstrate the evolutionary capacity of PSO and the efficiency of proposed local searches. In the second part, the proposed method is compared with a genetic algorithm from the literature. The results show that the method is competitive and efficient.

Genetic Algorithm for the Pick-up and Delivery Problem with Time Window by Multi-Compartment Vehicles

“…(Godart, 2019) made a new variant of the PDPTW which authorizes a multiple visit with a storage transfer by proposing a hybrid metaheuristic based on an evolutionary algorithm. (Peng et al, 2018) Worked on the Selective Pickup and Delivery Problem with Time Windows and Paired Demands (SPDPTWPD)". they found the optimal solution using '' particle swarm optimization (PSO) and compared it with a 'genetic algorithm.…”