The optimization of vehicle routing of communal waste in an urban environment using a nearest neighbirs' algorithm and genetic algorithm: Communal waste vehicle routing optimization in urban areas

Abstract

The current effects of rapid development, high population density in large residential areas and pressures on organizations to protect the environment, create a provocative framework for waste management in modern cities. The complexity of the process of garbage collection is large, and therefore a major concern for public authorities in terms of collection, transport and further processing of solid waste. In this paper, the authors have presented a two-step solution formed from a nearest neighbor search and genetic algorithm to optimize the path of trucks with a specified capacity for garbage collection. This method firstly performs a search for the optimal solution with a nearest neighbors' algorithm (NNA) over a set of possible solutions, and then in the second step gives that solution with other random solutions to a genetic algorithm (GA) for further improvement; the goal is to extract the solution with minimal trajectory and maximum capacity utilization of trucks that are available. Testing was done on a range of problems with a certain number of trucks, with a given capacity and the number and location of sites for waste collection.