Abstract
Vehicle Routing Problem (VRP) has become an integral part in logistic operations which determines optimal routes for several vehicles to serve customers. The basic version of VRP is Capacitated VRP (CVRP) which considers equal capacities for all vehicles. The objective of CVRP is to minimize the total traveling distance of all vehicles to serve all the customers. Various methods are used to solve CVRP, among them the most popular way is splitting the task into two different phases: assigning customers under different vehicles and then finding optimal route of each vehicle. Sweep clustering algorithm is well studied for clustering nodes. On the other hand, route optimization is simply a traveling salesman problem (TSP) and a number of TSP optimization methods are applied for this purpose. In Sweep, cluster formation staring angle is identified as an element of CVRP performance. In this study, a heuristic approach is developed to identify appropriate starting angle in Sweep clustering. The proposed heuristic approach considers angle difference of consecutive nodes and distance between the nodes as well as distances from the depot. On the other hand, velocity tentative particle swarm optimization (VTPSO), the most recent TSP method, is considered for route optimization. Finally, proposed adaptive Sweep (i.e., Sweep with proposed heuristic) plus VTPSO is tested on a large number of benchmark CVRP problems and is revealed as an effective CVRP solving method while outcomes compared with other prominent methods.
Highlights
Vehicle Routing Problem (VRP) has become an integral part in logistic operations which determines optimal routes for several vehicles to serve customers [1]
The objective of this study is to investigate effective
A two-phase Capacitated VRP (CVRP) solving method has been investigated through clustering with proposed adaptive Sweep and individual vehicle route optimizing with velocity tentative particle swarm optimization (VTPSO)
Summary
Vehicle Routing Problem (VRP) has become an integral part in logistic operations which determines optimal routes for several vehicles to serve customers [1]. A number of methods are available that optimizes customer assignment under vehicles and routes of the vehicles together [5]. This section explains proposed CVRP solving method using adaptive Sweep and VTPSO. To make the paper selfcontained, VTPSO, the considered TSP route optimization method, is explained briefly. CVRP solving method through adaptive Sweep where cluster starting angle is adaptive to problem. The most of the Sweep based methods, including the already discussed methods, considered standard Sweep for assigning customers under different vehicles and employed different methods to generate optimal routes for the vehicles. In standard Sweep, cluster formation starts from 00 and advances toward to assign all the nodes under different vehicles [7] Problem with such rigid starting is identified that total clusters formation may exceeds total number of available vehicles for some instances. CVRP problems and outcomes are compared with other prominent methods
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