The applications of multiple route optimization heuristics and meta-heuristic algorithms to solid waste transportation: A case study in Turkey

The dense population and high solid waste production make it challenging to determine the optimal routes for garbage collection trucks in metropolitan cities. Moreover, incorrectly planned routes cause waste of fuel, time, and other resources in the municipal garbage collection process. Vehicle Routing Problem (VRP) is a combinatorial optimization problem that aims to find optimal routes for a certain number of vehicles that start from a depot, visit all customers, and return to the depot. This study aims to find the optimal routes that satisfy all the needs by considering the waste collection process of the Istanbul Umraniye district. Data on the currently used routes, daily tonnages, number of truck trips, and the number and locations of containers in the Umraniye district were obtained from the Umraniye municipality. We solve the route optimization problem of the Umraniye municipality with multiple heuristics and meta-heuristic algorithms like the nearest neighbor, savings, Christofides, simulated annealing, greedy descent, guided local search, and Tabu Search algorithms. We show the examined heuristics and meta-heuristics can produce fast and feasible solutions to large-size real-life problems. •We present the applications of multiple route optimization heuristics and meta-heuristic algorithms to solid waste transportation.•The waste collection problem is considered a capacitated vehicle routing problem.•Real waste collection data from a district in Istanbul, Turkey, is used in this study.•Multiple heuristic and meta-heuristic algorithms are used to find the optimal route in this large-sized problem.