51,899 research outputs found

    Multi-behavior agent model for supply chain management

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    Recent economic and international threats to occidental industries have encouraged companies to rethink their planning systems. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and the need for collaboration. Thus, agility and the ability to deal quickly with disturbances in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network. This paper proposes a multi-behavior agent model using different decision making approaches in a context where planning decisions are supported by a distributed advanced planning system (d-APS). The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to the supply chain planning for the forest products industry

    Multi-Behavior Agent Model for Supply Chain Management

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    Recent economic and international threats to occidental industries have encouraged companies to rethink their planning systems. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and the need for collaboration. Thus, agility and the ability to deal quickly with disturbances in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network. This paper proposes a multi-behavior agent model using different decision making approaches in a context where planning decisions are supported by a distributed advanced planning system (d-APS). The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to the supply chain planning for the forest products industry

    Supply chain management of the Canadian Forest Products industry under supply and demand uncertainties: a simulation-based optimization approach

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    The Canadian forest products industry has failed to retain its competitiveness in the global markets under stochastic supply and demand conditions. Supply chain management models that integrate the two-way flow of information and materials under stochastic supply and demand can ensure capacity-feasible production of forest industry and achieve desired customer satisfaction levels. This thesis aims to develop a real-time decision support system, using simulation-based optimization approach, for the Canadian forest products industry under uncertain market supply and demand conditions. First, a simulation-based optimization model is developed for a single product (sawlogs), single industry (sawmill) under demand uncertainty that minimizes supply chain costs and finds optimum inventory policy parameters (s, S) for all agents. The model is then extended to multi-product, multi-industry forest products supply chain under supply and demand uncertainty, using a pulp mill as the nodal agent. Integrating operational planning decisions (inventory management, order and supply quantities) throughout the supply chain, the overall cost of the supply chain is minimized. Finally, the model integrates production planning of the pulp mill with inventory management throughout the supply chain, and maximizes net annual profit of the pulp mill. It was found that incorporation of a merchandizing yard between suppliers and forest mills provides a feasible solution to handle supply and demand uncertainty. Although the merchandizing yard increases the total daily cost of the supply chain by 11,802inthesingleindustrymodel,thereisanetannualcostsavingof11,802 in the single industry model, there is a net annual cost saving of 17.4 million in the multi-product, multi-industry supply chain. Under supply and demand uncertainty without a merchandizing yard, the pulp mill is only able to operate at 10% of its full capacity and achieve a customer satisfaction level of 9%. The merchandizing yard ensures pulp mill running capacity of 70%, and customer satisfaction level of at least 50%. However, the merchandizing yard is economically viable only, if the sales price of pulp is at least $680 per tonne. Efficient and effective management of inventory throughout the supply chain, integrated with production planning not only ensures continuous operation of forest mills, but also significantly improves the customer satisfaction

    Multi Site Coordination using a Multi-Agent System

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    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

    AI and OR in management of operations: history and trends

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    The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

    Exploring new forms of intermediation in the forest value chain

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    This paper proposes a method to restructure the forest value chain using intermediaries when a wider range of forest values should be managed for several stakeholders. This method leads to the definition of the strategic vision of the intermediary, including its value proposition and its required competencies, assuming that actors in the value chain are prepared to revise their business approach to enable effective collaboration and knowledge sharing. The method is used to support management of public forests in the Province of Quebec, in Eastern Canada. Basically, the intermediary, referred to as the integrator-supplier (IS) in the application case, enables several stakeholders, including the government, the forest industry, regional authorities, recreation organizations, and First Nations, to cnmmunicate, to set compatible goals, and to synchronize their activities. These activities and interactions must all be effectively carried out to maximize the overall benefits of forest management. Three critical issues for successful development of the IS are identified. The results present functional descriptions of seven development scenarios for effective use of intermediation in forest value chains

    Toward digital twins for sawmill production planning and control : benefits, opportunities and challenges

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    Sawmills are key elements of the forest product industry supply chain, and they play important economic, social, and environmental roles. Sawmill production planning and control are, however, challenging owing to severalfactors, including, but not limited to, the heterogeneity of the raw material. The emerging concept of digital twins introduced in the context of Industry 4.0 has generated high interest and has been studied in a variety of domains, including production planning and control. In this paper, we investigate the benefits digital twins would bring to the sawmill industry via a literature review on the wider subject of sawmill production planning and control. Opportunities facilitating their implementation, as well as ongoing challenges from both academic and industrial perspectives, are also studied

    Integrated methodological frameworks for modelling agent-based advanced supply chain planning systems: a systematic literature review

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    Purpose: The objective of this paper is to provide a systematic literature review of recent developments in methodological frameworks for the modelling and simulation of agent-based advanced supply chain planning systems. Design/methodology/approach: A systematic literature review is provided to identify, select and make an analysis and a critical summary of all suitable studies in the area. It is organized into two blocks: the first one covers agent-based supply chain planning systems in general terms, while the second one specializes the previous search to identify those works explicitly containing methodological aspects. Findings: Among sixty suitable manuscripts identified in the primary literature search, only seven explicitly considered the methodological aspects. In addition, we noted that, in general, the notion of advanced supply chain planning is not considered unambiguously, that the social and individual aspects of the agent society are not taken into account in a clear manner in several studies and that a significant part of the works are of a theoretical nature, with few real-scale industrial applications. An integrated framework covering all phases of the modelling and simulation process is still lacking in the literature visited. Research limitations/implications: The main research limitations are related to the period covered (last four years), the selected scientific databases, the selected language (i.e. English) and the use of only one assessment framework for the descriptive evaluation part. Practical implications: The identification of recent works in the domain and discussion concerning their limitations can help pave the way for new and innovative researches towards a complete methodological framework for agent-based advanced supply chain planning systems. Originality/value: As there are no recent state-of-the-art reviews in the domain of methodological frameworks for agent-based supply chain planning, this paper contributes to systematizing and consolidating what has been done in recent years and uncovers interesting research gaps for future studies in this emerging fieldPeer Reviewe
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