Bir gerçek hayat otobüs servis sisteminin simülasyon modellemesi ve ortalama seyahat süresinin simülasyon entegre metasezgisel algoritmalarla optimizasyonu

One of the important problems in the management of transportation systems is the bus scheduling problem. This problem is the problem of determining the most suitable departure schedule for buses with different passenger demands, different departure times and different routes. In this thesis, a stochastic simulation modelling structure has been developed to understand the dynamics of the system, to determine the outputs of the system under different parameters and to be an input to the optimization methods. The goal is to obtain a feasible bus schedule for all buses in the system and to minimize the average travel time of passengers. To obtain feasible bus schedule, four different metaheuristic optimization algorithms are integrated with the simulation model to minimize the average passenger travel time. The first algorithm is obtained by integrating simulation and genetic algorithm (GA), the second algorithm is obtained by integrating simulation and particle swarm (PS), the third algorithm is obtained by integrating simulation with ant colony (AC), and the fourth algorithm is obtained by integrating simulation and artificial bee (ABC). After developing the simulation models that reflects the system behaviours, the four algorithms mentioned are adapted to the scheduling problem and these algorithms are integrated with the simulation model to produce results by working simultaneously. These optimization algorithms are run to obtain a feasible bus schedule with the best average passenger travel time then the findings are compared and the results are discussed.