Optimizing the transportation system based on time and location of facilities in urban waste collection using the Internet of Things

Abstract

Today, the production of all kinds of waste and its environmental problems have made the management of urban services face many issues in the collection, transportation, and disposal of trash. Since the collection and transportation of waste occupies a significant part of the waste management budget, it seems necessary to use the appropriate method to reduce the collection costs. This research presents a mathematical model for garbage collection, which reduces the costs of collection and transportation by minimizing the distance traveled by trucks. Also, the model can collect the waste of a node in two or more separate times if needed. In this model, there is a non-uniform fixed fleet with a fixed number of each type of machine with different costs and capacities for each one. The overall goal is to minimize the cost of the fleet, the total distance of the trips, or its duration. The proposed model can create routes with the minimum number of vehicles' idle capacity and use time to serve all customers (nodes). To solve the presented model, a meta-innovative algorithm based on simulated annealing is proposed, which produces good solutions in a reasonable time. Several experimental problems in small and large dimensions are solved, and then the calculation results are presented. In conclusion, the performance of the proposed algorithm in the waste and garbage collection industry in a metropolis city is investigated. The results show that the proposed heuristic algorithms for generating the initial solution are very efficient for problems with small dimensions and produce the optimal solution. However, a meta-heuristic algorithm is needed for the problem with larger sizes.