چكيده به لاتين
Recently urbanization experienced a rapid growth. Because of high population lots of problems appeared, such as traffic jam, air pollution, accidents and high energy consumption. For city logistics distribution and urban transportation system as a remarkable energy consumer and polluter, saving energy and decreasing the pollutants specifically in metropolises with dense population is very important. City logistic models can be helpful in solving these complex problems. Paying attention to the gaps in existing research, a bi-objective mathematical model is presented In this research for minimizing the economical and environmental expenses and also for minimizing the response time. The proposed model makes decision on the problem of locating and allocating in city logistics distribution network. The network structure is so that the goods will be transferred through three levels: Logistics centers around the city are the first level, second level is distribution centers within the city and third level is sales terminals as demand areas. In fact, objective is choosing a number of fixed site to construct city distribution centers and how should be the allocation of sales terminals to distribution centers and allocation of distribution centers to logistics centers. The potential demand of goods is considered and network modeling is based on queue theory. The presented model has incorporated the carbon tax and sources with low carbon emission have been utilized in city distribution centers. Then a numerical example is generated in order to verify the model, and the results of solving the model using ε-Constraint method and sensitivity analysis are presented. Later, as a case study, the fruit distribution network in city of Tehran is presented using the model and also the existing information is designed. Finally the overall results of the research and future studies that can be considered are stated.
Keywords: City logistics, Urban freight distribution, Carbon emissions, City Distribution Centers, Network designing and planning, Queuing theory
