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

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.