scholarly journals A multi-agent systems approach for sustainable supplier selection and order allocation in a partnership supply chain

2018 ◽  
Vol 269 (1) ◽  
pp. 286-301 ◽  
Author(s):  
Pezhman Ghadimi ◽  
Farshad Ghassemi Toosi ◽  
Cathal Heavey
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Systems Approach ◽  
Multi Agent Systems ◽  
Order Allocation ◽  
Agent Systems ◽  
Sustainable Supplier Selection ◽  
Multi Agent

An agent-based supplier selection framework

2015 ◽  
Vol 8 (2/3) ◽  
pp. 180-205 ◽  
Author(s):  
Alireza Jahani ◽  
Masrah Azrifah Azmi Murad ◽  
Md. Nasir bin Sulaiman ◽  
Mohd. Hasan Selamat
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Information Overload ◽  
Case Based Reasoning ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Common Framework ◽  
Multi Agent ◽  
Case Based

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.

Intelligent Traceability System of Containerized Goods

2013 ◽  
Vol 309 ◽  
pp. 241-251 ◽  
Author(s):  
Mourad Abed ◽  
Imen Charfeddine ◽  
Mounir Benaissa ◽  
Marta Starostka-Patyk
Keyword(s):  
Supply Chain ◽  
Intelligent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Traceability System ◽  
Transport Chain ◽  
Multimodal Transport ◽  
Literature Reviews ◽  
Different Types ◽  
Multi Agent

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).

scholarly journals A multi-agent based system with big data processing for enhanced supply chain agility

2016 ◽  
Vol 29 (5) ◽  
pp. 706-727 ◽  
Author(s):  
Mihalis Giannakis ◽  
Michalis Louis
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Semantic Web ◽  
Supply Chains ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Agent Systems ◽  
Supply Chain Agility ◽  
Multi Agent

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

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