Clarke & Wright's Savings Algorithm and Genetic Algorithms Based Hybrid Approach for Flying Sidekick Traveling Salesman Problem

Abstract

Over the past few years, drones also known as unmanned aerial vehicles (UAV), have been adopted as a part of transportation activities in logistic sector. This paper investigates a new version of traveling salesman problem called as flying sidekick traveling salesman problem(FSTSP) in which trucks and drones serve the customers in coordination with the objective of minimizing the total delivery distance of trucks at the depot after completing the deliveries. Clarke & Wright's savings algorithm is a well-known heuristics approach in literature, which gives better solution for classical vehicle routing problem. In this paper, a hybrid approach based on Clarke & Wright's savings algorithm and genetic algorithm is proposed for solving the new version of travelling salesman problem. In the proposed hybrid algorithm, which is the sequential use of genetic algorithm and Clarke & Wright's savings algorithm, is used for assignment of the truck, drone or both of them to serve the customer. The solution of the genetic algorithm, which is the well-known metaheuristic approach, is enhanced with Clarke & Wright's savings algorithm. The aim of the problem is to minimize the total delivery distance according to the assignment decisions. This is the first hybrid approach in the literature including Clarke & Wright's savings algorithm and genetic algorithm that applies for FSTSP problem. The hypothetical experiments conducted on various instances and results confirm the efficiency of the approach and give some insights on this drone delivery system.