Fuzzy Inventory Carrying Optimize Its Intelligent Algorithm

Inventory Routing Problems(IRP) arises when both inventory and routing are incorporated in a model to adequately capture the characteristics of a distribution system. The reason we consider fuzzy inventory routing problems(FIRP) is that no historical data is available and some decision variables can't be expressed crisply. This paper considers Inventory Routing Problems(IRP) in which custom demand, travel times are fuzzy variables. A fuzzy optimization model is designed for Fuzzy Inventory Routing Problems(FIRP) with time window, then we integrated fuzzy simulation and ant-colony algorithm into a hybrid intelligent algorithm to solve the fuzzy vehicle routing model. In ant-colony algorithm, ants are divided into tow parts, ants in the first part are used to find paths of vehicle routing, and another kind of ants is devoted to get the quantity of delivery, optimal time cycle, vehicle start time etc. Finally, a numerical example is given to show the effectiveness of the algorithm.