Efficiency optimization of vehicle routing problem with considering IoT - a case study in Slovakia

Due to its complexity, vehicle routing is considered a challenging problem in the transportation and logistics area, because finding the best solution is considered almost impossible due to the amount of consumed time and limited resources. Therefore, optimization algorithms are used to find the optimal value or best possible solution within a relatively short time to reach the most effective and cost-efficient result, especially in the vehicles sector where cost and quality are both considered important factors. Optimization algorithms evolved from conventional mathematical methods to modern developed ones that use heuristic and metaheuristic approaches. IoT applications and developments show an interesting step forward in city logistics and transportation in general. IoT gives a big impact and potential for raising energy efficiency since it provides strong involvement as effective tools to get data and interact with it. In this article, the authors present a study that describes the effectiveness of four metaheuristic optimization algorithms next to present and analyze a case study in Slovakia where thirty locations in the city center of Kosice are used to solve the vehicle routing problem in two applications, direct TSP application and MTSP application with consideration for the IoT involvement. The optimization algorithms are analyzed and discussed by five benchmarks to compare the minimization results and execution time. The used model in the case study is described, and the four metaheuristic algorithms (GA, PSO, SA, and ACO) are compared against the nearest neighbor algorithm where they showed better results.