Authors: Peter Kwasi Sarpong1, Andrew Owusu-Hemeng2, Joseph Ackora-Prah3
1,2,3Department of Mathematics, Kwame Nkrumah University of Science and Technology,Kumasi,Ghana
Email: owusuhemengandrew@gmail.com, kp.sarp@yahoo.co.uk, ackph@yahoo.co.uk
Abstract
The Vehicle Routing Problem (VRP) can be solved using Genetic Algorithm (GA) because the wholesale points under focus here are random. The main objective or goal here is to find the minimum total distribution distance by the vehicle to N different wholesale locations. Upon studying the operations of Amponsah Effah Pharmaceutical Limited (Kumasi) carefully, the operations of this company is to distribute their medicine after production to their nineteen (19) wholesale points starting from their depot in Adum to different cities with their delivery vehicle. Since the wholesale points of the company are sited in random cities and the delivery vehicle have to distribute the medicines without passing through a specific route, their operations can be modeled by Vehicle Routing Problem. A data was collected from Amponsah Effah Pharmaceutical Limited which has been used to create a set of routes on which the company uses to minimize the total distribution distance of the vehicle. Testing every probability for N wholesale tour would be . This implies that testing 19 wholesale points including their main depot in Adum making it 20 tour, we would have to measure different tours. To calculate the fittest of tours for its minimum distance would take years. However, genetic algorithm can be used to find a solution in the shortest possible time, although it might not find the best solution, it can find a near perfect solution for a 100 wholesale tour in less than a minute. There are couples of basic steps to solving the vehicle routing problem using GA which has been discussed below.
Keywords: Genetic Algorithm, Vehicle Routing Problem
