International Journal of New Technology and Research (IJNTR) ISSN: 2454-4116, Volume-2, Issue-10, October 2016 Pages 36-39 36 www.ijntr.org Abstract — Contemporary Supply Chain (SC) networks are complex and dynamic environments comprising of stakeholders and their fragile relationships, along with the associated interconnecting products, cash and information flows. The main objective of the SC is the creation of added value at every single node of the network. In terms of coordination, taking into account the dynamic nature of SCs, central coordination techniques are considered of high risk, as they are not resistant to changes and have a single point of failure. Decentralized management is a precondition for creating flexible and effective networks, as nodes need to dynamically move in and out of the SC and every node has a decision-making ability. Decentralized networks have no single point of failure, as every node can support the decision-making process according to the actual state of the network. Agent-based (AB) simulation platforms create decentralized networks of peer nodes, provide native mechanisms of communication and coordination techniques and are suitable for simulating the complex nature of SCs. In this paper, we first provide a literature review on AB simulation software used in supply chains modeling, we then describe an illustrative case study, and finally we develop two AB models using two distinct software platforms. The present work highlights the use of AB platforms agrifood supply chain modeling and can be used by academicians and practitioners as a practical example in order to incorporate AB techniques into the SC. The model-building details are provided for both platforms, as well as a critical analysis of the implemented models. The results demonstrate the incorporation of AB platforms to the SC ecosystem and compare the Agent-Based Modeling (ABM) capabilities of the alternative software platforms. Index Terms—Agent-Based Simulation, Agent-Based Modeling, Agrifood Supply Chains I. INTRODUCTION System modeling could potentially involve (i) process-based approaches that analyze the system's processes, (ii) analytical solutions with the use of complex mathematical models, and (iii) simulation techniques (Labarthe et al, 2007). Discrete event and Agent- Based Modeling (ABM) are considered among the most cited simulation techniques. Supply Chains (SCs) are complex and dynamic networks that encounter significant changes over time. Agents, on the other hand, are autonomous entities that can act on behalf of Christos Keramydas, Department of Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece. Dimitrios Bechtsis, Department of Automation Engineering, Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, Greece. Dimitrios Aidonis, Department of Logistics, Technological Educational Institute of Central Macedonia, Katerini, Greece. real world actors and thus dynamically support the associated decision-making processes, taking into consideration both local and global knowledge about their environment. The nature of the SC promotes the use of agents as each SC stakeholder can be represented with an autonomous agent (Fig. 1). Figure 1. SC Stakeholders acting as autonomous agents AB simulation has been identified as a useful tool to the development of certain decision-making processes in SCs mainly due to its somewhat “natural” correspondence between SC stakeholders and agents. The capability of representing the interactions between stakeholders over time, in a dynamic and distributed environment, is unique at the agent society. The AB approach allows for observing the behavior of each supply chain stakeholder over time, as well as of the SC as a whole. Multi-Agent System (MAS) platforms are composed of multiple agents that negotiate and cooperate in order to obtain their goals (O’Hare and Jennings, 1996). The MAS model could be implemented at (i) the Java Agent Development Framework (JADE) and (ii) the NetLogo Framework. The remainder of the manuscript is organized as follows. In Section II we describe AB platforms that can be applied to the SC ecosystem. In Section III, we analyze the proposed model and we present two distinct AB implementations. Finally, in Section IV we wrap-up with conclusions and critical discussion. II. AGENT BASED PLATFORMS A. Agent-Based Modeling Frameworks The development of AB models is crucial for the proper and error-prone functionality of the final system. AB platforms allow for the rapid development of models with the use of inherent functions that implement the AB functionalities (behaviors, communication and coordination techniques, protocols, agent templates, etc.). The most cited Agent-Based Simulation for Modeling Supply Chains: A Comparative Case Study Keramydas Christos, Bechtsis Dimitrios, Aidonis Dimitrios