Abstract
The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To get solutions in determining routes which are realistic and very close to the actual solution, we use heuristics and metaheuristics which are of the combinatorial optimization type. A literature review of VRPTW, TDVRP, and a metaheuristic such as the genetic algorithm was conducted. In this paper, the implementation of the VRPTW and its extension, the time-dependent VRPTW (TDVRPTW) has been carried out using the model as well as metaheuristics such as the genetic algorithm (GA). The algorithms were implemented, using Matlab and HeuristicLab optimization software. A plugin was developed using Visual C# and DOT NET framework 4.5. Results were tested using Solomon’s 56 benchmark instances classified into groups such as C1, C2, R1, R2, RC1, RC2, with 100 customer nodes, 25 vehicles and each vehicle capacity of 200. The results were comparable to the earlier algorithms developed and in some cases the current algorithm yielded better results in terms of total distance travelled and the average number of vehicles used.
Highlights
Vehicle Routing Problem (VRP) is one of the most important topics in operations research
VRP is closely related to TSP, and according to Bullheimer et al [1], as soon as the customers of the VRP are assigned to vehicles, the problem is reduced to several or multiple TSPs
The Vehicle Routing Problem (VRP) is used to design an optimal route for a fleet of vehicles, to service a set of customers given a set of constraints
Summary
Vehicle Routing Problem (VRP) is one of the most important topics in operations research. As we can see the vehicles originate at the depot, visit all the nodes once, fulfill their demands at the nodes and return to the depot once again. The VRP is used in supply chain management in the physical delivery of goods and services. There are several variants to the VRP. These are formulated based on the nature of the transported goods, the quality of service required and the characteristics of the customers and the vehicles.
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