Inventory routing problems (IRP) are among important tools to be used for implementing vendor manage inventory. Many researchers try to develop methods for solving inventory routing problem, however, only a few developed methods for inventory routing problems for spoilage items. In reality, many items are deteriorated and spoiled during transportation and storage period. In this paper, we developed a model and methods to solve the inventory routing problem for deteriorating items with dynamic demand and spoilage rate, i.e., demand varies and items spoil during planning periods. Those cases are more realistic since many commodities such as fruits and vegetables have dynamic demand and spoilage rate. A Genetic Algorithm and Particle Swarm Optimization are developed to solve the problem with various demands in a specific planning period since the problem is Np-hard. A numerical example and sensitivity analysis are con- ducted to verify the model, and to get management insight it. The result is interesting and support general hypothesis that dynamic demands result in higher inventory cost than the static demands, and the increasing demand results in increasing inventory cost. Also, the results show that increasing demand and deteriorating rates significantly affect the total cost, therefore, the developed model is important and significantly useful to be used for solving IRP with dynamic demand and spoilage items.