Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.cor.2007.01.027
Title: Real-time supply chain control via multi-agent adjustable autonomy
Authors: Lau, H.C.
Agussurja, L. 
Thangarajoo, R. 
Keywords: Crisis management
Fuzzy controller
Military warehouse
Multi-agent system
Real-time control
Issue Date: Nov-2008
Citation: Lau, H.C., Agussurja, L., Thangarajoo, R. (2008-11). Real-time supply chain control via multi-agent adjustable autonomy. Computers and Operations Research 35 (11) : 3452-3464. ScholarBank@NUS Repository. https://doi.org/10.1016/j.cor.2007.01.027
Abstract: Real-time supply chain management in a rapidly changing environment requires reactive and dynamic collaboration among participating entities. In this work, we model supply chain as a multi-agent system where agents are subject to an adjustable autonomy. The autonomy of an agent refers to its capability to make and influence decisions within a multi-agent system. Adjustable autonomy means changing the autonomy of the agents during runtime as a response to changes in the environment. In the context of a supply chain, different entities will have different autonomy levels and objective functions as the environment changes, and the goal is to design a real-time control technique to maintain global consistency and optimality. We propose a centralized fuzzy framework for sensing and translating environmental changes to the changes in autonomy levels and objectives of the agents. In response to the changes, a coalition-formation algorithm will be executed to allow agents to negotiate and re-establish global consistency and optimality. We apply our proposed framework to two supply chain control problems with drastic changes in the environment: one in controlling a military hazardous material storage facility under peace-to-war transition, and the other in supply management during a crisis (such as bird-flu or terrorist attacks). Experimental results show that by adjusting autonomy in response to environmental changes, the behavior of the supply chain system can be controlled accordingly. © 2007 Elsevier Ltd. All rights reserved.
Source Title: Computers and Operations Research
URI: http://scholarbank.nus.edu.sg/handle/10635/112992
ISSN: 03050548
DOI: 10.1016/j.cor.2007.01.027
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