چكيده به لاتين
Development of an integrated public transport system in order to respond to growing demand and increasing the utility of public transportation in major cities, is inevitable. In this system, along with the rapid mass modes, modes with lower capacity and speed, such as feeder network to increase accessibility and provide demand massive modes are used for both.In this paper, a method for designing a network of feeder lines, provided that its demand for feeder stations have a probability distribution. In this research, a method for designing a feeder network base on probabilistic demand provided. The objective function is to minimize user, operation and social costs. Due to the complexity of the problem, a meta-heuristic algorithm and universal generating function method is used to solve the problem.The model has been implemented on a hypothetical network. In order to study the effect of probabilistic distribution in feeder network design, seven scenarios based on demand changes are considered and used in the design of network. Furthermore design results are compared with deterministic demand model. In all scenarios the network cost in proportion to deterministic model cost increases and increasing stations demand causes overall increase in network cost. Network routing in each scenario is variable depending on stations demand. In probabilistic model in proportion to deterministic model, network required frequencies increases and in result users cost decreases and operator cost, which is estimated in design stage, increases.
Keywords: public transportation, feeder, probabilistic demand, ant colony algorithm
