A comparative study on the selection of the most suitable route for the collection and transportation of municipal solid waste

Abstract

Worldwide, approximately US$410 billion is spent annually on the management of four billion tons of domestic solid waste (MSW). The transportation cost alone accounts for more than 50% of the total expenditure on solid waste management. This cost constitutes approximately 85% of the collection and transportation cost. 54.4% of environmental protection expenditures cover waste services. The population of the Barış neighborhood in the Kayapınar district of Diyarbakır, which is the subject of this study, is 23 581 according to the 2020 TUIK data. The average amount of waste produced per person in a month is 7.6 kg/person. In the results of these statistics, it has been seen that the investment costs in the transportation of wastes are increasing day by day. In this study, the performance of ant colony and genetic algorithms, which are among the artificial intelligence techniques, and route optimization using GIS (geographic information system) software were tried to be achieved to solve the GSP (traveling salesman problem), which is included in the route planning problems. The results of the study showed that savings were achieved with an improvement of 15.1576% in GIS, 29.8104% in GA (Genetic algorithm) and 40.5171% in ACS (Ant Colony System) compared to real life. As a result of the application, it has been observed that the ant colony algorithm is superior to the Genetic algorithm and GIS, as it draws a shorter route in terms of distance and obtains a better result in terms of improvement rate.