In order to enable both manufacturers and suppliers to be profitable on today’s highly competitive markets, manufacturers and suppliers must be quick in selecting best partners establishing strategic relationship, an...In order to enable both manufacturers and suppliers to be profitable on today’s highly competitive markets, manufacturers and suppliers must be quick in selecting best partners establishing strategic relationship, and collaborating with each other so that they can satisfy the changing competitive manufacturing requirements. A web-based supplier relationships (SR) framework is therfore proposed using multi-agent systems and linear programming technique to reduce supply cost, increase flexibility and shorten response time. Web-based SR approach is an ideal platform for information exchange that helps buyers and suppliers to maintain the availability of materials in the right quantity, at the right place, and at the right time, and keep the customer-supplier relationship more transparent. A multi-agent system prototype was implemented by simulation, which shows the feasibility of the proposed architecture.展开更多
Suitable rescue path selection is very important to rescue lives and reduce the loss of disasters, and has been a key issue in the field of disaster response management. In this paper, we present a path selection algo...Suitable rescue path selection is very important to rescue lives and reduce the loss of disasters, and has been a key issue in the field of disaster response management. In this paper, we present a path selection algorithm based on Q-learning for disaster response applications. We assume that a rescue team is an agent, which is operating in a dynamic and dangerous environment and needs to find a safe and short path in the least time. We first propose a path selection model for disaster response management, and deduce that path selection based on our model is a Markov decision process. Then, we introduce Q-learning and design strategies for action selection and to avoid cyclic path. Finally, experimental results show that our algorithm can find a safe and short path in the dynamic and dangerous environment, which can provide a specific and significant reference for practical management in disaster response applications.展开更多
文摘In order to enable both manufacturers and suppliers to be profitable on today’s highly competitive markets, manufacturers and suppliers must be quick in selecting best partners establishing strategic relationship, and collaborating with each other so that they can satisfy the changing competitive manufacturing requirements. A web-based supplier relationships (SR) framework is therfore proposed using multi-agent systems and linear programming technique to reduce supply cost, increase flexibility and shorten response time. Web-based SR approach is an ideal platform for information exchange that helps buyers and suppliers to maintain the availability of materials in the right quantity, at the right place, and at the right time, and keep the customer-supplier relationship more transparent. A multi-agent system prototype was implemented by simulation, which shows the feasibility of the proposed architecture.
基金supported by National Basic Research Program of China (973 Program) (No. 2009CB326203)National Natural Science Foundation of China (No. 61004103)+5 种基金the National Research Foundation for the Doctoral Program of Higher Education of China (No. 20100111110005)China Postdoctoral Science Foundation (No. 20090460742)National Engineering Research Center of Special Display Technology (No. 2008HGXJ0350)Natural Science Foundation of Anhui Province (No. 090412058, No. 070412035)Natural Science Foundation of Anhui Province of China (No. 11040606Q44, No. 090412058)Specialized Research Fund for Doctoral Scholars of Hefei University of Technology (No. GDBJ2009-003, No. GDBJ2009-067)
文摘Suitable rescue path selection is very important to rescue lives and reduce the loss of disasters, and has been a key issue in the field of disaster response management. In this paper, we present a path selection algorithm based on Q-learning for disaster response applications. We assume that a rescue team is an agent, which is operating in a dynamic and dangerous environment and needs to find a safe and short path in the least time. We first propose a path selection model for disaster response management, and deduce that path selection based on our model is a Markov decision process. Then, we introduce Q-learning and design strategies for action selection and to avoid cyclic path. Finally, experimental results show that our algorithm can find a safe and short path in the dynamic and dangerous environment, which can provide a specific and significant reference for practical management in disaster response applications.
