Abstract
The Capacitated Vehicle Routing Problem is the most common and basic variant of the vehicle routing problem, where it represents an important problem in the fields of transportation, distribution and logistics. It involves finding a set of optimal routes that achieve the minimum cost and serve scattered customer locations under several constraints such as the distance between customers’ locations, available vehicles, vehicle capacity and customer demands. The Cluster first – Route second is the proposed approach used to solve capacitated vehicle routing problem which applied in a real case study used in that research, it consists of two main phases. In the first phase, the objective is to group the closest geographical customer locations together into clusters based on their locations, vehicle capacity and demands by using Sweep algorithm. In the second phase, the objective is to generate the minimum cost route for each cluster by using the Nearest Neighbor algorithm. The hybrid approach is evaluated by Augerat’s Euclidean benchmark datasets.
Highlights
The Vehicle Routing Problems (VRP) are Nondeterministic Polynomial-time (NP) hard optimization problems
The proposed approach that's based on hybrid Sweep Algorithm and Nearest Neighbor Algorithm (SA & NNA) was coded in C# on an Intel Core i3-2350M CPU 230 GHz with 3.00 GB of RAM under Windows 8 platform
After clustering process is performed by using the sweep algorithm, the optimal routes achieved by using a nearest neighbor algorithm
Summary
The Vehicle Routing Problems (VRP) are Nondeterministic Polynomial-time (NP) hard optimization problems. Its objective is to plan a tour under several constraints for a fleet of vehicles, that can be homogeneous or heterogeneous, the tour represents the best routes between scattered locations or customer nodes with minimum travelling cost. The capacitated vehicle routing problem (CVRP) is a generalization of VRP which represents the most elementary version of the vehicle routing problem. In CVRP model, a fleet of vehicles, located at single or multiple depots need to be scheduled to satisfy the customers’ demands, while visiting every customer exactly once and the capacity of the vehicles must not be exceeded at any point in time. The objective is to obtain a solution that either minimizes the number of vehicles and/or total travelling cost (time or distance)
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