Supply chain cluster cost synergy management using a multi-agent intelligent system

Author(s):  
Yuanlue Fu ◽  
Jianxi Fu
2013 ◽  
Vol 309 ◽  
pp. 241-251 ◽  
Author(s):  
Mourad Abed ◽  
Imen Charfeddine ◽  
Mounir Benaissa ◽  
Marta Starostka-Patyk

In recent year, many countries across in the world have made traceability a compulsory procedure in the Supply Chain. The Supply Chain is distributed collaborative environments involves the acquisition and use of extensive informational and physical flows. The flows management seems a complex task for the actors of the multimodal transport chain which the transport is the major driver in a Supply Chain. The literature reviews throws light on the traceability in the Supply Chain Management (SCM) shows the lack of interoperability and flexibility in data management systems hinders the work of traceability. And it introduces the importance and complexity of multimodal transport operations. To ensure effective traceability all along this chain, we relied on the agent paradigm and the ontology which facilitate the integration of goods data in order to exploit and reuse. Indeed, to ensure communication and interoperability of these data we relied on Multi-Agent Systems, due to their characteristics of autonomy, sociability and responsiveness that are generally associated. The Multi-Agent Systems can build flexible systems whose behaviors are complex and complicated due to the combination of different types of agents. With a focus on the importance of the concept of the traceability, the objective of this work is to propose an intelligent system for the traceability of containerized goods in the context of multimodal transport: Intelligent Traceability System of Containerized Goods (i-TSCG).


Author(s):  
Wei Zhou ◽  
Maha Saad Metawea

As is known that, one of the challenges in ensuring the quality and safety of agricultural products in China is how to organize plenty of scattered small farmers and integrate them into the modern agricultural products supply chain system. In this paper, in order to promote the tight integration of agricultural products supply chain, based on multi-agent system, a computer simulation model of agricultural products supply chain is proposed. Through a series of simulation experiments, the evolution of the organizational structure of the agricultural products supply chain, its impact on the quality and safety of agricultural products under different government regulations are explored and discussed in detail. It follows from these simulation results that the more long-term-contract farmers and sellers, the more conducive to the improvement of the quality and safety of agricultural products, and the corresponding countermeasures and suggestions are also provided.


2015 ◽  
Vol 8 (2/3) ◽  
pp. 180-205 ◽  
Author(s):  
Alireza Jahani ◽  
Masrah Azrifah Azmi Murad ◽  
Md. Nasir bin Sulaiman ◽  
Mohd. Hasan Selamat

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.


2012 ◽  
Vol 135 (1) ◽  
pp. 468-478 ◽  
Author(s):  
Lorena A. Bearzotti ◽  
Enrique Salomone ◽  
Omar J. Chiotti

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