چكيده به لاتين
Hub Location problem is one of the optimization problems used extensively. There are a set of points in this problem forming supplier and demander networks of which their goods must be transported. The purpose of this problem is to select one or several intermediate points among the existing points as a hub. Hence, instead of connecting all points directly, goods transportation is carried out through these intermediate points (hub).
In this research, logistics hubs of loads in the country have been located according to uncertainty in amount of the load. Therefore, after deterministic modeling of the problem, a non-deterministic model of hub location was developed. Regarding uncertainty situations and the long-time nature of the problem, the stochastic process was separated using two-step stochastic programming. For this purpose, after collecting the freight transportation data, necessary parameters for determining the distribution function between every two source and destination points were extracted and various scenarios were developed. According to developed scenarios, forecasted values of the amount of load in the future were used as the inputs of the problem. Using this method, existing non-deterministic problem has been transformed into a deterministic one and techniques of solving deterministic problems have been used to solve it by means of the standard optimization software. To investigate the performance of the proposed model, a group containing seven provinces in the central region of Iran were selected, past trend of transportation among these provinces were modeled in the stochastic process and different scenarios were developed for the future years. After solving the problem, results showed that establishing two hubs in Qom and Tehran will have the minimum cost.
After the sensitivity analysis, it was concluded that impact of the number of hubs on transportation cost is more than the value of α coefficient.
Keywords: Hub Location Problem, Uncertainty, Stochastic Programming, Transportation.
