An Agent-Based Solution for Dynamic Supply Chain Management

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dc.creatorPodobnik,Vedran
dc.creatorPetric,Ana
dc.creatorJezic,Gordan
dc.date2008
dc.date.accessioned2024-02-06T12:56:30Z
dc.date.available2024-02-06T12:56:30Z
dc.descriptionSupply chain management (SCM) deals with planning and coordinating activities such as material procurement, product assembly, and the distribution of manufactured products. This paper offers an agent-based solution as a potentially adequate approach for the automation of supply chain management. The greatest obstacle in SCM research is obtaining benchmark designed solutions since it is difficult to simulate real business environments, while live testing in real-world systems is not an option. The Trading Agent Competition Supply Chain Management (TAC SCM) scenario provides a unique testbed for studying and prototyping SCM agents by providing a challenging game environment where competing agents engage in complex decision-making activities with the purpose of maximizing their profit. In this paper, we describe the TAC SCM environment and present the main features of the CrocodileAgent, our TAC SCM 2007 entry. Additionally, the CrocodileAgent s performance in the competition, as well as in a series of controlled experiments, is discussed.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-014-07-1080
dc.identifierhttps://lib.jucs.org/article/29031/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/9688
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 14(7): 1080-1104
dc.subjectsupply chain management
dc.subjectelectronic markets
dc.subjectsoftware agents
dc.subjecttrading agents
dc.subjectmulti-agent simulation
dc.titleAn Agent-Based Solution for Dynamic Supply Chain Management
dc.typeResearch Article
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