Abstract
Logistics networks face the contradictory requirements of achieving high operational effectiveness and efficiency while retaining the ability to adapt to a changing environment. Changing customer demands and network participants entering or leaving the system cause these dynamics and hamper the collection of information which is necessary for efficient process control. Decentralized approaches representing logistics entities by autonomous artificial agents help coping with these challenges. Coordination of these agents is a fundamental task which has to be addressed in order to enable successful logistics operations. This paper presents a novel approach to self-organization for multiagent system coordination. The approach avoids a priori assumptions regarding agent characteristics by generating expectations solely based on observable behavior. It is formalized, implemented, and applied to a logistics network scenario. An empirical evaluation shows its ability to approximate optimal supply network configurations in logistics agent coordination.
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Berndt, J.O. (2013). Self-Organizing Logistics Process Control: An Agent-Based Approach. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2011. Communications in Computer and Information Science, vol 271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29966-7_26
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DOI: https://doi.org/10.1007/978-3-642-29966-7_26
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