Integrated methodological frameworks for modelling agent-based advanced supply chain planning systems: A systematic literature review

• Main Authors: Luis Antonio Santa-Eulalia, Georgina Halladjian, Sophie D'Amours, Jean-Marc Frayret
• Format: Article
• Language: English
• Published: OmniaScience 2011-12-01
• Series: Journal of Industrial Engineering and Management
• Subjects: supply chain management, advanced supply chain planning systems, agent-based modelling and simulation, methodological frameworks.
• Online Access: http://www.jiem.org/index.php/jiem/article/view/326

<p><strong>Purpose:</strong> The objective of this paper is to provide a systematic literature review of recent developments in methodological frameworks for the modelling and simulation of agent-based advanced supply chain planning systems.</p><p><strong>Design/methodology/approach:</strong> A systematic literature review is provided to identify, select and make an analysis and a critical summary of all suitable studies in the area. It is organized into two blocks: the first one covers agent-based supply chain planning systems in general terms, while the second one specializes the previous search to identify those works explicitly containing methodological aspects.</p><p><strong>Findings:</strong> Among sixty suitable manuscripts identified in the primary literature search, only seven explicitly considered the methodological aspects. In addition, we noted that, in general, the notion of advanced supply chain planning is not considered unambiguously, that the social and individual aspects of the agent society are not taken into account in a clear manner in several studies and that a significant part of the works are of a theoretical nature, with few real-scale industrial applications. An integrated framework covering all phases of the modelling and simulation process is still lacking in the literature visited.</p><p><strong>Research limitations/implications:</strong> The main research limitations are related to the period covered (last four years), the selected scientific databases, the selected language (i.e. English) and the use of only one assessment framework for the descriptive evaluation part.</p><p><strong>Practical implications: </strong>The identification of recent works in the domain and discussion concerning their limitations can help pave the way for new and innovative researches towards a complete methodological framework for agent-based advanced supply chain planning systems.</p><p><strong>Originality/value: </strong>As there are no recent state-of-the-art reviews in the domain of methodological frameworks for agent-based supply chain planning, this paper contributes to systematizing and consolidating what has been done in recent years and uncovers interesting research gaps for future studies in this emerging field.</p>