scholarly journals Will bots take over the supply chain? Revisiting Agent-based supply chain automation

2021 ◽  
pp. 108279
Author(s):  
Liming Xu ◽  
Stephen Mak ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Agent Based

scholarly journals An Agent-Based Model for Supply Chain Recovery in the Wake of the COVID-19 Pandemic

2021 ◽  
pp. 107401
Author(s):  
Towfique Rahman ◽  
Firouzeh Taghikhah ◽  
Sanjoy Kumar Paul ◽  
Nagesh Shukla ◽  
Renu Agarwal
Keyword(s):  
Supply Chain ◽  
Agent Based Model ◽  
Agent Based

A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems

2008 ◽  
Vol 34 (3) ◽  
pp. 1680-1691 ◽  
Author(s):  
M.H. Fazel Zarandi ◽  
M. Pourakbar ◽  
I.B. Turksen
Keyword(s):  
Supply Chain ◽  
Bullwhip Effect ◽  
Agent Based Model ◽  
Agent Based

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.

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