Auction Bidding Methods for Multiagent Consensus Optimization in Supply–Demand Networks
| Autor: | Ilya Buzytsky, Andrey Shishkarev, Ashis G. Banerjee, Jundi Liu, Niyousha Rahimi |
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| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization Computer science Supply chain Distributed computing media_common.quotation_subject Autonomous agent Biomedical Engineering 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Supply and demand 020901 industrial engineering & automation Artificial Intelligence Manufacturing Quality (business) 0101 mathematics Information exchange media_common business.industry Mechanical Engineering Multi-agent system Bidding Computer Science Applications Human-Computer Interaction Control and Systems Engineering Computer Vision and Pattern Recognition business |
| Zdroj: | IEEE Robotics and Automation Letters. 3:4415-4422 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2018.2869999 |
| Popis: | Multiagent systems are characterized by decentralized decision-making by the (semi)autonomous agents and localized communication or information exchange among the neighboring agents. Supply–demand networks form the backbones of both services and manufacturing industries, and need to operate as efficiently as possible to yield optimized returns. In this letter, we bring the notion of multiagent systems to clustered supply–demand networks such that each supplier acts as an agent. Consequently, we adapt consensus-based auction bidding methods to optimize the assignment of demands to the suppliers with known communication pathways and resource constraints. Results on moderately large networks show promising performance in terms of both assignment quality, as given by the overall demand delivery cost and proportion of assigned demands, and computation time. |
| Databáze: | OpenAIRE |
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