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Innovar
Print version ISSN 0121-5051
Abstract
HERNANDEZ, Jorge E; ALEMANY, M.M.E; LARIO, Francisco C and POLER, Raúl. SCAMM-CPA: A supply chain agent-based modelling methodology that supports a collaborative planning process. Innovar [online]. 2009, vol.19, n.34, pp.99-120. ISSN 0121-5051.
Multi-agent system technologies are currently becoming a strong modelling tool for supporting the complexities present in planning supply chains. As supply chains are composed by nodes needing common agreement to fulfil their own requirements, the multi-agent system thus represents a suitable tool for modelling negotiation, mainly within a collaborative context. Nevertheless, a review of the relevant literature revealed a certain deficiency in existing agent-based modelling methodologies supporting collaborative supply chain planning. This paper has thus proposed a novel agent-based modelling methodology to cover such deficiency to make a real contribution towards supply chain agent-based modelling within a collaborative planning environment. This methodology was supported by the relevant aspects found in the literature review regarding collaborative planning within a multi-agent context (agent definition, scope, decisional level, distribution and supply chain network entities, modelling technique, interaction, coordination mechanism, advantages and disadvantages) and explicit methodologies supporting the agent-based modelling of any type of problem under consideration. By considering the corresponding literature review, the proposed new methodology synthesised existing knowledge in the field and both fulfilled and enriched each of its phases with our own modellers' knowledge. This study adopted a static view of a real automotive supply chain network so as to present a first real multi-agent-based supply chain model approach as an application of this novel modelling methodology.
Keywords : multi-agent system (MAS); collaborative planning (CP); collaborative operational planning (COP); modelling methodology; supply chain management (SCM); distribution and supply chains and networks (DSC-N); literature review.