Abstract
The Capacitated Vehicle Routing Problem (CVRP) is an optimization problem owing to find minimal travel distances to serve customers with homogeneous fleet of vehicles. Clustering customers and then assign individual vehicles is a widely-studied way, called cluster first and route second (CFRS) method, for solving CVRP. Cluster formation is important between two phases of CFRS for better CVRP solution. Sweep (SW) clustering is the pioneer one in CFRS method which solely depends on customers’ polar angle: sort the customers according to polar angle; and a cluster starts with customer having smallest polar angle and completes it considering others according to polar angle. On the other hand, Sweep Nearest (SN) algorithm, an extension of Sweep, also considers smallest polar angle customer to initialize a cluster but inserts other customer(s) based on the nearest neighbor approach. This study investigates a different way of clustering based on nearest neighbor approach. The proposed Distance based Sweep Nearest (DSN) method starts clustering from the farthest customer point and continues for a cluster based on nearest neighbor concept. The proposed method does not rely on polar angle of the customers like SW and SN. To identify the effectiveness of the proposed approach, SW, SN and DSN have been implemented in this study for solving benchmark CVRPs. For route optimization of individual vehicles, Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization are considered for clusters formation with SW, SN and DSN. The experimental results identified that proposed DSN outperformed SN and SW in most of the cases and DSN with PSO was the best suited method for CVRP.
Highlights
The Vehicle Routing Problem (VRP) can be depicted as the issue of structuring ideal conveyance routes from one or a few warehouses to various geologically dissipated urban areas or clients while keeping up certain imperatives [1].Capacitated VRP (CVRP) is one of the most studied variations of VRP with an extra limitation of fixed vehicle conveying limit [2]
The experimental results identified that proposed Distance based Sweep Nearest (DSN) outperformed Sweep Nearest (SN) and SW in most of the cases and DSN with Particle Swarm Optimization (PSO) was the best suited method for Keywords—Capacitated vehicle routing problem; sweep algorithm; sweep nearest algorithm; genetic algorithm; ant colony optimization; particle swarm optimization
This study investigates a different way of clustering based on nearest neighbor approach
Summary
The Vehicle Routing Problem (VRP) can be depicted as the issue of structuring ideal conveyance routes from one or a few warehouses to various geologically dissipated urban areas or clients while keeping up certain imperatives [1]. In solving CVRP, constructive and clustering methods are commonly used in the heuristic approaches to construct the routes. All the customers are gathered into different groups using a clustering algorithm and after that an optimization algorithm used to make route of individual clusters. A cluster is made by sweeping the customers as per their polar angle (expanding or diminishing request). K. Shin [10] introduced cluster adjustment approach in Sweep and route generated with LinKernighan heuristic method. This study investigates a different way of clustering based on nearest neighbor approach. Sweep Nearest (DSN) method starts clustering from the farthest customer point and continue for a cluster based on nearest neighbor concept. For route optimization of individual vehicles, Genetic Algorithm, Ant. Colony Optimization and Particle Swarm Optimization are considered for clusters formation with SW, SN and DSN.
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