DocumentCode
2850043
Title
A Game Theoretic Approach for Resource Allocation Based on Ant Colony Optimization in Emergency Management
Author
Wang, Zhiyong ; Xu, Weisheng ; Yang, Jijun ; Peng, Jiazhen
Author_Institution
Sch. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
fYear
2009
fDate
19-20 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
In the context of multiple emergencies occurring simultaneously, the optimal allocation of relief resources to multiple emergency locations is a challenging issue in emergency management. This work presents a noncooperative complete information game model for resource allocation and an algorithm for calculating Nash equilibrium (NE). In this model, the players represent the multiple emergency locations, strategies correspond to possible resource allocations, and the payoff is modeled as function of the cost of allocation and the amount of resources requested. Thus, the optimal results are determined by the Nash equilibrium of this game. Then we design an improved ant colony optimization (ACO) algorithm to obtain the Nash equilibrium by introducing dynamic random search technique. Experimental results show that the proposed model is effective in optimizing resource allocation during multiple emergencies for emergency management decision support.
Keywords
emergency services; game theory; optimisation; resource allocation; Nash equilibrium; ant colony optimization; dynamic random search technique; emergency management; game theoretic approach; multiple emergency location; noncooperative complete information game model; resource allocation; Algorithm design and analysis; Ant colony optimization; Availability; Cost function; Disaster management; Engineering management; Game theory; Heuristic algorithms; Nash equilibrium; Resource management;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4994-1
Type
conf
DOI
10.1109/ICIECS.2009.5365328
Filename
5365328
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