compartments of the ships. Due to the fact that the proposed MIP cannot be solved on time, a heuristic is proposed.Different from the traditional approach, Novaes et al. (2009) consider in its analysis a dynamic environment for urban routing problem subject to traffic jams. Using the concepts of Sequential Analysis, the study comprises a warehouse and a homogeneous fleet of vehicles serving a certain urban region. Each vehicle is designated for a district, leaving the warehouse in the morning, performing the designated orders (tasks), returning in the end of the day to the warehouse. From a dynamic point of view, part of the planned service is addressed to other agents (vehicles) when the system judges the need, avoiding that the tasks are not performed.As observed, there are different approaches for the transportation problem, involving several sources, destinations, companies and products. A possible manner to model the maritime transportation problem for the Brazilian exportation of manufactured products is by the recent application of Autonomous Agents. In the following item it is presented the concept of Autonomous Agents applied to logistic problems.4. Application of the Autonomous Agents concept in the resolution of transport logistics problemsThe most part of data process systems and logistics systems comprise several components, treated as agents, which usually actuates in an autonomous manner, which can also communicate and interact with the others, forming a network. Therefore, the Autonomous Agents form a community in a common environment where they actuate and transform based on rules, in order to reach their individual objectives. Besides being a new approach to logistics, several studies have been developed by the Collaborative Research Centre 637 Autonomous Cooperating Logistic Processes group in Bremen, Germany, with the purpose of detecting when and how the autonomous control can present more advantages than the classic control, especially regarding time, costs and robustness.4.1 Autonomous agent conceptAccording to Holscher et al., 2007 each autonomous agent has a goal, rules and control conditions and manage, in an autonomous manner, the application of rules in order to complete the established objective. The fact that the agents are based on rules provides basis for the dynamic of processes.One direct explanation of its use in the logistics problem is handling each container, truck, company and ship as an autonomous agent, with rules to be observed in order to reach its individual goals (for example: the goal of the container is leaving from company A and arriving at destination B within Z days). With such information, the agents analyze, in an autonomous manner, the possibilities of actuation and take their decisions. Such feature allows the creation of a decentralized system, but still with autonomy. The transport network is a graphic where the nodes represent locations; which means, warehouses, where the packets (goods) can be collected or delivered. The edges represent the connections between the warehouses. Each edge is labeled with the time required for travel through the connection represented by the edge. Trucks and packets are modeled as autonomous agents. Instances of these Autonomous Agents are represented as special nodes with single identifiers. In the example presented