Optimization of capacitated vehicle routing problem using initial route with same size K-means and greedy algorithm for vaccines distribution

Abstract

Vaccines are the solution that is currently underway to tackle COVID-19. In this paper, vaccine distribution for hospitals in Central Java is developed. The problem case in this paper is classified as a Capacitated Vehicle Routing Problem (CVRP). The method proposed is using an initial route that follows the cluster-first route-second method (CFRS). The same size K-means is used for the clustering phase and the Greedy algorithm is used for the routing phase. The result of the initial route is a clustered route for each vehicle with a balanced capacity. Then, each cluster was re-optimized using metaheuristics Guided Local Search from Google OR-tools. Our experiment results have proven that using the initial route has the effect of reducing runtime by 97.37% - 99.17% when compared to without the initial route. This is because using initial routes with the same size K-means means breaking the problem into parts, then using the Greedy algorithm can reduce the number of possible routes. However, the total distance increased by 8.22% - 16.69% because no cluster member is allowed to move to another cluster.