Design of Multi-Behavior Agents for Supply Chain Planning: An Application to the Lumber Industry

Forget, Pascal; Gaudreault, Jonathan

doi:10.5772/5359

Cited by 5 publications

(5 citation statements)

References 30 publications

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“…However, a promising solution to an individual service may not necessarily be a good choice from the viewpoint of a global solution. The goal of supply chain integration is to design and operate the entire chain so that total chain-wide performance is maintained (Forget et al, 2008). Function surfaces in such complex problems can be very rugged due to a number of dimensions.…”

Section: Selection Of Promising Solutions As the Argumentsmentioning

confidence: 99%

“…To model and simulate complex supply chains in a mass customization context, Labarthe et al (2007) proposed a methodological framework based on an agent paradigm. Forget et al (2008) explored a framework to design multi-agent behavior in a supply chain planning system, where agents were able to dynamically change their planning and coordination mechanism and, ultimately increase overall performance. Most work in this area has concerned with distributed planning and scheduling system that models the supply chain as a set of semi-autonomous and collaborative entities acting together to coordinate their decentralized plans (Lendermann et al, 2001;Baumgaertel and John, 2003).…”

Section: Agent-based Approaches In Supply Chain Managementmentioning

confidence: 99%

“…The ability to select suitable partners and effectively utilize their resources throughout the chain is a key to successful supply chain networks (Kumar and BecerraFernandez, 2007). To achieve this, it is crucial to rapidly identify suitable resources (partners or services) and effectively coordinate them through the formation process, where various constraints such as service capacity, quality, cost, timeliness, and interdependencies between services need to be taken into account (Forget et al, 2008;Wang et al, 2008). The constraint may be limited to an individual service, called an intra-service constraint (e.g., the quantity of the components to be purchased in a procurement service), or related to more than one service, called inter-service constraints (e.g., a manufacturing service should be scheduled to start after the procurement service is completed).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Agent-based negotiation and decision making for dynamic supply chain formation

Wang

Vogel

et al. 2009

Engineering Applications of Artificial Intelligence

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Section: Selection Of Promising Solutions As the Argumentsmentioning

confidence: 99%

Section: Agent-based Approaches In Supply Chain Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Agent-based negotiation and decision making for dynamic supply chain formation

Wang

Vogel

et al. 2009

Engineering Applications of Artificial Intelligence

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“…To overcome this problem, companies are required to coordinate their supply, production and order fulfillment processes effectively across their supply chains within a comprehensive framework. In addition, many constraints such as price, time, quality and service level as well as numerous functions, such as sales, design, inventory, manufacturing, procurement and buying, must be considered (Forget et al, 2008, Sadeh et al, 2001. Furthermore, when companies implement information technologies (IT), all channel information, transactions and decisions can be interconnected.…”

Section: Introductionmentioning

confidence: 99%

An agent-based supplier selection framework

Jahani

Murad

Sulaiman

et al. 2015

Strategic Outsourcing: An International Journal

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Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.

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“…To model and simulate complex supply chains in a mass customization context, Labarthe et al (2007) proposed a methodological framework based on an agent paradigm. Forget et al (2008) explored a framework to design multi-agent behavior in a supply chain planning system, where agents were able to dynamically change their planning and coordination mechanism and, ultimately increase overall performance. Min and Bjornsson (2000) presented a conceptual model of agent-based supply chain automation, in which a project agent gathers actual construction progress information and sends to subcontractor agents and supplier agents, respectively, over the Internet.…”

Section: Introductionmentioning

confidence: 99%