Optimizing routes of municipal waste collection: an application algorithm

Abstract

PurposeThe purpose of this study is to formulate an algorithm designed to discern the optimal routes for efficient municipal solid waste (MSW) collection.Design/methodology/approachThe research method is simulation. The proposed algorithm combines heuristics derived from the constructive genetic algorithm (CGA) and tabu search (TS). The algorithm is applied in a municipality located at Southern Brazil, with 40,000 inhabitants, circa.FindingsThe implementation achieved a remarkable 25.44% reduction in daily mileage of the vehicles, resulting in savings of 150.80 km/month and 1,809.60 km/year. Additionally, it reduced greenhouse gas emissions (including fossil CO2, CH4, N2O, total CO2e and biogenic CO2) by an average of 26.15%. Moreover, it saved 39 min of daily working time.Research limitations/implicationsFurther research should thoroughly analyze the feasibility of decision-making regarding planning, scheduling and scaling municipal services using digital technology.Practical implicationsThe municipality now has a tool to improve public management, mainly related with municipal solid waste. The municipality reduced the cost of public management of municipal solid waste, redirecting funds to other priorities, such as public health and education.Originality/valueThe study integrates MSW collection service with an online platform based on Google MapsTM. The advantages of employing geographical information systems are agility, low cost, adaptation to changes and accuracy.