Abstract
The Transportation Planning (TP) is well-known basic network problem which can be defined as the problem that calculates the optimal amount of deliveries. But for some real-world applications, it is often that the TP model is extended to satisfy other additional constraints or performed in several stages. In addition, the concept of inventory and time are not included. Moreover, today's distribution channel becomes a flexible form. In this study, we formulate a flexible logistics network model with concept of inventory and time. The purpose of this model is minimization of the total cost that includes inventory cost. Moreover, the network form has flexible connection and a certain period divided into some terms. To solve the problem, we propose the hybrid Genetic Algorithms (hGA) approach by using a priority-based encoding method. Finally, numerical experiments with various scales of logistics network problems are used to show the effectiveness and the efficiency of our approach.
