Open AccessDevelopment of Particle Swarm Optimization and Simulated Annealing Algorithms to Solve Vehicle Routing Problems with Drones
Author(s) -
Hasan Aji Prawira,
Budi Santosa
Publication year - 2021
Publication title -
prozima (productivity, optimization, and manufacturing system)
Language(s) - English
Resource type - Journals
ISSN - 2541-5115
DOI - 10.21070/prozima.v5i1.1398
Subject(s) - drone , truck , simulated annealing , particle swarm optimization , vehicle routing problem , computer science , swarm behaviour , routing (electronic design automation) , mathematical optimization , algorithm , engineering , automotive engineering , mathematics , artificial intelligence , computer network , biology , genetics
Vehicle Routing Problem with Drone (VRPD) is a problem of determining the number of routes for delivery of goods from the depot to a number of customers using trucks and drones. Drones are an alternative delivery tool besides trucks, each truck can be equipped with a support drone. Drones can be used to make a delivery while the truck is making others. By combining a truck and a drone, the truck can act as a tool for drone launch and landing so that the drones can reach long distances from the depot. The purpose of this problem is to minimize the cost of sending goods by trucks and drones. In this study, the Particle Swarm Optimization (PSO) and the Simulated Annealing (SA) are proposed to solve these problems. The Route Drone algorithm are used to help change the structure of the PSO and SA solutions into a VRPD solution. The proposed algorithm has been applied to 24 different scenarios ranging from 6 customers to 100 customers. The PSO and SA algorithms are able to find solutions that are close to optimal. The SA is able to find a better solution than the PSO.