Multi Site Coordination using a Multi-Agent System

A new approach of coordination of decisions in a multi site system is proposed. It is based this approach on a multi-agent concept and on the principle of distributed network of enterprises. For this purpose, each enterprise is defined as autonomous and performs simultaneously at the local and global levels. The basic component of our approach is a so-called Virtual Enterprise Node (VEN), where the enterprise network is represented as a set of tiers (like in a product breakdown structure). Within the network, each partner constitutes a VEN, which is in contact with several customers and suppliers. Exchanges between the VENs ensure the autonomy of decision, and guarantiee the consistency of information and material flows. Only two complementary VEN agents are necessary: one for external interactions, the Negotiator Agent (NA) and one for the planning of internal decisions, the Planner Agent (PA). If supply problems occur in the network, two other agents are defined: the Tier Negotiator Agent (TNA) working at the tier level only and the Supply Chain Mediator Agent (SCMA) working at the level of the enterprise network. These two agents are only active when the perturbation occurs. Otherwise, the VENs process the flow of information alone. With this new approach, managing enterprise network becomes much more transparent and looks like managing a simple enterprise in the network. The use of a Multi-Agent System (MAS) allows physical distribution of the decisional system, and procures a heterarchical organization structure with a decentralized control that guaranties the autonomy of each entity and the flexibility of the network

The organization of transactions research with the Trust and Tracing Game

This paper presents empirical results of research on the influence of social aspects on the organization of transactions in the domain of chains and networks. The research method used was a gaming simulation called the Trust and Tracing game in which participants trade commodity goods with a hidden quality attribute. Previous sessions of this gaming simulation identified a list of variables for further investigation (Meijer et al., 2006). The use of gaming simulation as data gathering tool for quantitative research in supply chains and networks is a proof-of-principle. This paper shows results from 27 newly conducted sessions and previously unused data from 3 older sessions. Tests confirmed the use of network and market modes of organization. Pre-existing social relations influenced the course of the action in the sessions. Being socially embedded was not beneficial for the score on the performance indicators money and points. The hypothesized reduction in measurable transaction costs when there was high trust between the participants could not be found. Further analysis revealed that participants are able to suspect cheats in a session based on other factors than tracing. Testing hypotheses with data gathered in a gaming simulation proved feasible. Experiences with the methodology used are discusse

An agent-based dynamic information network for supply chain management

One of the main research issues in supply chain management is to improve the global efficiency of supply chains. However, the improvement efforts often fail because supply chains are complex, are subject to frequent changes, and collaboration and information sharing in the supply chains are often infeasible. This paper presents a practical collaboration framework for supply chain management wherein multi-agent systems form dynamic information networks and coordinate their production and order planning according to synchronized estimation of market demands. In the framework, agents employ an iterative relaxation contract net protocol to find the most desirable suppliers by using data envelopment analysis. Furthermore, the chain of buyers and suppliers, from the end markets to raw material suppliers, form dynamic information networks for synchronized planning. This paper presents an agent-based dynamic information network for supply chain management and discusses the associated pros and cons

A demand-driven approach for a multi-agent system in Supply Chain Management

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit. © 2010 Springer-Verlag Berlin Heidelberg

Collaborative Models for Supply Networks Coordination and Healthcare Consolidation

This work discusses the collaboration framework among different members of two complex systems: supply networks and consolidated healthcare systems. Although existing literature advocates the notion of strategic partnership/cooperation in both supply networks and healthcare systems, there is a dearth of studies quantitatively analyzing the scope of cooperation among the members and its benefit on the global performance. Hence, the first part of this dissertation discusses about two-echelon supply networks and studies the coordination of buyers and suppliers for multi-period procurement process. Viewing the issue from the same angel, the second part studies the coordination framework of hospitals for consolidated healthcare service delivery. Realizing the dynamic nature of information flow and the conflicting objectives of members in supply networks, a two-tier coordination mechanism among buyers and suppliers is modeled. The process begins with the intelligent matching of buyers and suppliers based on the similarity of users profiles. Then, a coordination mechanism for long-term agreements among buyers and suppliers is proposed. The proposed mechanism introduces the importance of strategic buyers for suppliers in modeling and decision making process. To enhance the network utilization, we examine a further collaboration among suppliers where cooperation incurs both cost and benefit. Coalitional game theory is utilized to model suppliers\u27 coalition formation. The efficiency of the proposed approaches is evaluated through simulation studies. We then revisit the common issue, the co-existence of partnership and conflict objectives of members, for consolidated healthcare systems and study the coordination of hospitals such that there is a central referral system to facilitate patients transfer. We consider three main players including physicians, hospitals managers, and the referral system. As a consequence, the interaction within these players will shape the coordinating scheme to improve the overall system performance. To come up with the incentive scheme for physicians and aligning hospitals activities, we define a multi-objective mathematical model and obtain optimal transfer pattern. Using optimal solutions as a baseline, a cooperative game between physicians and the central referral system is defined to coordinate decisions toward system optimality. The efficiency of the proposed approach is examined via a case study

Collaborative and adaptive supply chain planning

Dans le contexte industriel d'aujourd'hui, la compétitivité est fortement liée à la performance de la chaîne d'approvisionnement. En d'autres termes, il est essentiel que les unités d'affaires de la chaîne collaborent pour coordonner efficacement leurs activités de production, de façon a produire et livrer les produits à temps, à un coût raisonnable. Pour atteindre cet objectif, nous croyons qu'il est nécessaire que les entreprises adaptent leurs stratégies de planification, que nous appelons comportements, aux différentes situations auxquelles elles font face. En ayant une connaissance de l'impact de leurs comportements de planification sur la performance de la chaîne d'approvisionnement, les entreprises peuvent alors adapter leur comportement plutôt que d'utiliser toujours le même. Cette thèse de doctorat porte sur l'adaptation des comportements de planification des membres d'une même chaîne d'approvisionnement. Chaque membre pouvant choisir un comportement différent et toutes les combinaisons de ces comportements ayant potentiellement un impact sur la performance globale, il est difficile de connaître à l'avance l'ensemble des comportements à adopter pour améliorer cette performance. Il devient alors intéressant de simuler les différentes combinaisons de comportements dans différentes situations et d'évaluer les performances de chacun. Pour permettre l'utilisation de plusieurs comportements dans différentes situations, en utilisant la technologie à base d'agents, nous avons conçu un modèle d'agent à comportements multiples qui a la capacité d'adapter son comportement de planification selon la situation. Les agents planificateurs ont alors la possibilité de se coordonner de façon collaborative pour améliorer leur performance collective. En modélisant les unités d'affaires par des agents, nous avons simulé avec la plateforme de planification à base d'agents de FORAC des agents utilisant différents comportements de planification dits de réaction et de négociation. Cette plateforme, développée par le consortium de recherche FORAC de l'Université Laval, permet de simuler des décisions de planification et de planifier les opérations de la chaîne d'approvisionnement. Ces comportements de planification sont des métaheurisciques organisationnelles qui permettent aux agents de générer des plans de production différents. La simulation est basée sur un cas illustrant la chaîne d'approvisionnement de l'industrie du bois d'œuvre. Les résultats obtenus par l'utilisation de multiples comportements de réaction et de négociation montrent que les systèmes de planification avancée peuvent tirer avantage de disposer de plusieurs comportements de planification, en raIson du contexte dynamique des chaînes d'approvisionnement. La pertinence des résultats de cette thèse dépend de la prémisse que les entreprises qui adapteront leurs comportements de planification aux autres et à leur environnement auront un avantage concurrentiel important sur leurs adversaires

Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems

As the business environment gets more complicated, organizations must be able to respond to the business changes and adjust themselves quickly to gain their competitive advantages. This study proposes an integrated agent system, called SPA, which coordinates simulated and physical agents to provide an efficient way for organizations to meet the challenges in managing supply chains. In the integrated framework, physical agents coordinate with inter-organizations\' physical agents to form workable business processes and detect the variations occurring in the outside world, whereas simulated agents model and analyze the what-if scenarios to support physical agents in making decisions. This study uses a supply chain that produces digital still cameras as an example to demonstrate how the SPA works. In this example, individual information systems of the involved companies equip with the SPA and the entire supply chain is modeled as a hierarchical object oriented Petri nets. The SPA here applies the modified AGNES data clustering technique and the moving average approach to help each firm generalize customers\' past demand patterns and forecast their future demands. The amplitude of forecasting errors caused by bullwhip effects is used as a metric to evaluate the degree that the SPA affects the supply chain performance. The experimental results show that the SPA benefits the entire supply chain by reducing the bullwhip effects and forecasting errors in a dynamic environment.Supply Chain Performance Enhancement; Bullwhip Effects; Simulated Agents; Physical Agents; Dynamic Customer Demand Pattern Discovery

Method and Approach Mapping of Fair and Balanced Risk and Value-added Distribution in Supply Chains: A Review and Future Agenda

This paper proposes a fair and balanced risk and value-added distribution as a novel approach for collaborative supply chain. The objective of this article is to analyze the existing methods and approaches for risk management, value-adding, risk and revenue sharing to develop a new framework for balancing risk and value-adding in collaborative supply chains. The authors reviewed and synthesized 162 scientific articles which were published between 2001 and 2017 and. The reviewed articles were categorized into supply chain management and performance, risk management, value-added, fair risk and value-added distribution and supply chain negotiation. The potentials identified for future research were the importance of decision-making and sustainability for effectiveness of supply chain risk management. Most previous authors have applied an approach of revenue and risk-- sharing with both decentralized and centralized supply chains to achieve the fair risk and value-added distribution. The dominant methods we found in literature were game theory and complex mathematical formulation. Most literature focused on operation research techniques. We identified a lack of discussion of the intelligent system approach and a potential for future exploration. This paper guide future research and application agenda of fair risk and value-added distribution in supply chain collaboration. We developed a new framework for a fair and balanced risk and value-added distribution model. For a future agenda, we point towards the development of a systematic intelligent system applying soft-computing techniques and knowledge transfer for maintaining sustainable supply chains.Keywords Supply chain collaboration, Fair risk and value-added distribution, Revenue sharing, Risk management, Risk sharin

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing