A Novel Ant Colony optimization Algorithm for Waste Collection Problem

Waste management, especially waste collection issue, has been an ultimate global issue. Particularly, problem of collecting waste in minimum time, especially in big cities, becomes a challenge that needs solution. In this paper, this problem is approached by a well-known problem called Vehicle Routing Problem (VRP). The objective is to generate collision-free trajectories along the process of collection while minimizing the traveling time of the slowest vehicle. A novel method to solve such the problem, namely, Augmented-Node-based Ant Colony optimization (ANACO), is introduced. The main feature of this method is the generation oftrajectories, i.e., paths and velocities, of all waste collection vehicles. The advantage of the proposed method is in the ability to provide velocity information besides path, which is totally different from the typical ACO algorithms that only provide path information. By the proposed method, the traveling time of the slowest vehicle can be minimized. Therefore, the requirement of fast-collecting capability can be satisfied. Simulation results are presented proving that a minimum-time and collision-free trajectories can be generated to solve the problem.