An Agent-Based Supplier Selection Framework: A Case-Based Reasoning Approach

Jahani, Alireza; Murad, Masrah Azrifah Azmi; Sulaiman, Md. Nasir; Selamat, Hazlina

doi:10.1007/978-3-642-22603-8_24

Cited by 7 publications

(12 citation statements)

References 15 publications

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“…Added to the above studies, [35] brought forward a method that combined three supporting perspectives, which are multi-agent systems, fuzzy logic and case-based reasoning, a rare combination in one framework. The authors conducted an exploratory case study directed towards an office furniture firm to illustrate the value and effectiveness of their study framework.…”

Section: A Case-based Reasoning In Automated Knowledgementioning

confidence: 99%

Automated Knowledge Acquisition Framework for Supply Chain Management based on Hybridization of Case based Reasoning and Intelligent Agent

Almuiet¹,

Al-Zawahra²

2019

ijacsa

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Throughout the past few years, there has been notable research effort directed towards developing automated knowledge acquisition (KA) in order to automate knowledge acquisition in Supply Chain Management (SCM) applications. Several methods utilized for the automation of supply chain management involved Intelligent Agent (IA) and Case-Based Reasoning (CBR). This paper used both approaches to bring about automated knowledge acquisition in order to assist decision-making in SCM applications. With the arrival of a new case, prior cases are retrieved from the database and the potential solutions are laid down. After the completion of acquisition, case and solution outcome are analyzed and evaluated according to function similarity. Finally, after evaluating the new case along with the problem details and the chosen solution, the case is retained in the database for issues that will arise in future applications.

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Section: A Case-based Reasoning In Automated Knowledgementioning

confidence: 99%

Automated Knowledge Acquisition Framework for Supply Chain Management based on Hybridization of Case based Reasoning and Intelligent Agent

Almuiet¹,

Al-Zawahra²

2019

ijacsa

View full text Add to dashboard Cite

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“…Many researchers have tried to use agent technology in manufacturing integration, scheduling, control, inventory management, supply sourcing, SCM, mass customization, negotiation, information transfer and knowledge management within supply chain applications (Jahani et al, 2011). These attempts have led authors to categorize them into three generations of study: first, in manufacturing integration; second, supply chain integration; and finally, supply chain negotiation and knowledge management initiatives.…”

Section: Related Workmentioning

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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“…Consequently, frequent interactions with the customer are compelling SCs used to design novel business strategies to increase flexibility and adaptability, and to face the fierce worldwide competition. As Jahani et al (2015) stated: "unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today's supply chains". In this sense, relationship-based strategies can be promising.…”

Section: Introductionmentioning

confidence: 99%

“…Agents can work jointly as problem solvers through competition or cooperation to resolve issues that are beyond their individual capabilities (O'Hare et al, 1996). When studying the supplier selection process, agent-based approaches are widely used (Chen et al, 2016;Ghadimi et al, 2018;Jahani et al, 2015;Pourabdollahi et al , 2017;Valluri & Croson, 2005;Yang & Kao, 2009). This paper makes the following main contributions:…”

Section: Introductionmentioning

confidence: 99%

Advanced supplier selection: A hybrid multi-agent negotiation protocol supporting supply chain dyadic collaboration

Nejma¹,

Zair²,

Cherkaoui³

et al. 2019

10.5267/j.dsl

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This paper proposes a novel form of supplier selection involving the supply chain dyad as the buyer and the suppliers as sellers. The main proposed contribution is a multi-attribute decision hybrid protocol for supplier selection based on collaboration and negotiation, adapted to dyadic collaboration in a supply chain context. Suppliers and the purchasing dyad can reach an agreement on the details of the products simultaneously and exploit the preferences of the customer dyadic partner to enlarge the criteria choices of the products. For this, the proposed protocol combines a one-to-one bilateral dyadic collaboration protocol inside the purchasing dyad along with a one-to-many multi-bilateral bargaining protocol between the purchasing dyad and suppliers. Illustrative multi-agent simulation experiments were carried out to prove the effectiveness of the proposed protocol. The protocol implementation shows better negotiation results than the classic supplier selection process, along with expected higher customer partner satisfaction and a more embedded dyadic relationship. .

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An Agent-Based Supplier Selection Framework: A Case-Based Reasoning Approach

Cited by 7 publications

References 15 publications

Automated Knowledge Acquisition Framework for Supply Chain Management based on Hybridization of Case based Reasoning and Intelligent Agent

Automated Knowledge Acquisition Framework for Supply Chain Management based on Hybridization of Case based Reasoning and Intelligent Agent

An agent-based supplier selection framework

Advanced supplier selection: A hybrid multi-agent negotiation protocol supporting supply chain dyadic collaboration

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