SGA: spatial GIS-based genetic algorithm for route optimization of municipal solid waste collection

Designing optimization models and meta-heuristic algorithms for minimization of traveling routes of vehicles in solid waste collection has been gaining interest in environmental modeling. The computer models and methods are useful to bring out specific strategies for prevention and precaution of possible disasters that could be foreseen worldwide. This paper proposes a new Spatial Geographic Information System (GIS)-based Genetic Algorithm for optimizing the route of solid waste collection. The proposed algorithm, called SGA, uses a modified version of the original Dijkstra algorithm in GIS to generate optimal solutions for vehicles. Then, a pool of solutions, which are optimal routes of all vehicles, is encoded in Genetic Algorithm. It is iteratively evolved to a better one and finally to the optimal solution. Experiments on the case study at Sfax city in Tunisia are performed to validate the performance of the proposal. It has been shown that the proposed method has better performance than the practical route and the original Dijkstra method.