Determination of Malatya Metropolitian Municipality pesticide vehicles with metaheuristic algorithms

In this thesis, a multistage application has been developed to optimize the routes of the pesticide vehicles of Malatya Metropolitan Municipality with metaheuristic methods and the results have been shared. In the first stage of multistage application, the optimum distribution and routing of the neighborhoods to the vehicles has been made considering the related constraints. At this stage, the problem is the Vehicle Routing Problem with Time Window which is the type of vehicle routing problem and it has been solved using Genetic Algorithm (GA). In the second stage, the areas which were obtained as a result of the routing in the first stage are considered as the region and it is aimed that the spraying vehicles will travel the streets / roads in these regions with minimum distance. At this second stage, the problem is the Chinese Postman Problem (CPP) which is one of the problems of arc routing and it has been solved using Artificial Bee Colony (ABC) Algorithm. The most important step of the CPP is the minimum matching of odd degree nodes. In this study, it is modified to the parameter change part of ABC algorithm to provide minumum matching. Thus, optimum matching is achieved successfully even in very large graphs and the modification made to ABC algorithm has been introduced into the literature. Later, on Eulerian graphs obtained for regions with the optimum matching, Euler tour routes have been obtained. The neighborhoods distance matrix and the street / road distance matrices which is the data of the multistage application, were constituted for this study with the QGIS software from the geographic information system (GIS) software and are the real, original data. This multistage application has been applied on these distance matrices and optimum results have been obtained. KEYWORDS: Vehicle Routing, Arc Routing, Chinese Postman Problem, Eulerian Graph, Euler Tour, Metaheuristic Methods, Genetic Algorithm, Artificial Bee Colony Algorithm, Optimization, Georgraphic Information Systems, QGIS Software.