of abstraction), so the SD and ABMS approaches fit better in these problems.4.1 System DynamicsDeveloped by Forrester (1961), SD studies the behavior of systems over time, containing two fundamental languages: causal diagrams and stock-flows. Both of them allow the modeler graphically represent the system being modeled (Sterman, 2000). For the purpose to exemplify the SD application, Silva et al. (2011) presents a possible causal-diagram to model the hole of collaboration in the manufactured goods exportation process. See Figure 2.Figure 2 - Reinforcing and balancing loopings between manufactured goods exporters and maritime carriers negotiationSource: Silva et al. (2011)Considering the first step when modelling with SD is to define the systems boundary, the aforementioned authors considered as agents only the manufactured goods industries and the maritime carriers. Such consideration represents a simplification of the system showed in Figure 1. The next step was to define the objectives of the agents and the main variables which influence these objectives. The manufactured goods industries aim to increase their competitiveness in the market and reduce logistics costs, while the maritime carriers aim to reduce the transportation offer-demand gap and to increase their profit. These objectives can be reached based on the actions of both agents: increasing collaboration among the export industries and changing the maritime transportation offer, as is showed in the Balancing and Reinforcing loopings in Figure 2.4.2 Agent-based Modelling SimulationThis method is widely used to understand and analyze systems with several interacting active objects generally when there is a decentralized decision-making. The main idea of this method is to consider the interrelations among the several components of a system. In such consideration the system is greater than the simple sum of its components (North and Macal (2007). In general, these components are named agents and they have their own set of rules and behaviors, which provides them the ability to affect in greater or lesser degree the systems global behavior.For the purpose to exemplify the ABMS application Figure 3 (developed by Silva et al., 2011) shows an UML class diagram as a possible form to model the role of collaboration in the manufactured goods exportation process. Figure 3 - Agent UML class diagram Source: Silva et al. (2011)Considering there is not an ABMS pattern model to represent a system, the above diagram was built following the steps proposed by Macal and North (2006):a. Agents: Identification of agents types and other objects (classes) along with their attributes - industry, NVOCC, 3PL, maritime carrier, land carrier and customer.b. Environment: Define the environment where the agents will live in and interact with - the market where the agents negotiate the transportation.c. Agent Methods: Specify the methods by which agents attributes are updated in response to either agent-to-agent interactions or agents interactions with the environment at every time period must be solved the following sequence: search a partner, choose a NVOCC and/or a carrier and finally, send the shipment. d. Agent Interactions: Add the methods that control which agents interact, when they interact and how they interact during the simulation - an interaction can be the choice of a