Parallel Hybrid Genetic Algorithm and GIS Based Optimization for Municipal Solid Waste Collection Routing

OpenAlex English

A vast majority of studies on municipal solid waste (MSW) collection routing do not consider the constraints pertinent to actual road networks such as unidirectional roads and terrain characteristics. As a result, good practices such as the avoidance of U-turns cannot be used. This study introduces geographic information system (GIS)-integrated software (RouteSW) for the optimization of MSW collection routes by considering path constraints. The software uses a parallelized hybrid genetic algorithm (PHGA) to obtain the optimal routes. The accuracy of the optimization algorithm is verified based on four asymmetric traveling salesman benchmark problems. Then, RouteSW is applied to generate the MSW collection routes in the Bahcelievler and Emek districts of Ankara (Turkey) for two different optimization models; Model A and Model B. Model A minimizes the total length of the collection route. Model B additionally takes road inclinations and collection truckloads into account in minimizing the total length traveled. Results indicate that although Model B produces longer paths compared with Model A, it prevents waste collection uphill when the collection truck is loaded. For both models, U-turns are avoided as aimed. Routes are displayed in a three-dimensional (3D) terrain view for each MSW collection truck. Service orders of MSW collection points are indicated in the display as well for each collection truck.