There would always be a lot of crisis locations when an unconventional emergency breaks out. The requirements of each crisis location are usually different, which is difficult to meet the requirements of multiple crisis locations for a single resource centre. So it is a practical problem to be solved urgently by decision makers how to fairly and reasonably schedule emergency resources for multiple crisis locations. According to the demand information, the dynamic process of emergency resources scheduling for multiple crisis locations are described, in which the emergency resources scheduling process are divided into several stages according to the change of demand information for multiple crisis locations. On this basis, a theoretical model of multi-stage emergency resources scheduling process is designed for multiple crisis locations. After a series of assumptions are made, the game model based on resource requirements of multiple crisis locations is set up by using game theory according to the degree of disaster, and the improved ant colony optimization (ACO) is introduced to seek out the solution in order to schedule emergency resources for multiple crisis locations according to the minimum virtual cost. Simulation tests and numerical analyses are given to demonstrate the feasibility and availability of the model. The model and algorithm can also provide a new solution and approach for the distribution of resources in business logistics.
YANG Ji-jun, SHE Lian
. Game Model and Optimization Based on Resource Requirements of Multiple Crisis Locations[J]. Chinese Journal of Management Science, 2016
, 24(8)
: 154
-163
.
DOI: 10.16381/j.cnki.issn1003-207x.2016.08.019
[1] Shetty R, Gupta U. An automated decision support system based on game theoretic optimization for emergency management in urban[J]. Journal of Homeland Security and Emergency Management, 2007, 4(2): 1-25.
[2] Shetty R. An event driven single game solution for resource allocation in a multi-crisis environment[D]. Tampa: University of South Florida, 2004.
[3] Wang Susheng, Wang Yan, Sun Jian. An optimized emergency resources allocation algorithm for large-scale public emergency[C]//Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, August 19-22, 2007.
[4] Rubel D, Shinya H. An agent-based model for resource allocation during relief distribution[J]. Journal of Humanitarian Logistics and Supply Chain Management, 2014, 4(2): 265-285.
[5] 王苏生, 王岩. 基于公平优先原则的多受灾点应急资源配置算法[J]. 运筹与管理, 2008, 17(3): 16-21.
[6] 杨勃, 杜冰, 李小林. 多受灾点救灾物资分配调度问题启发式算法[J]. 系统工程, 2012, 30(1): 97-102.
[7] 王旭坪, 董莉, 陈明天. 考虑感知满意度的多受灾点应急资源分配模型[J]. 系统管理学报, 2013, 22(2): 251-256.
[8] 詹沙磊, 刘南. 基于灾情信息更新的应急物资配送多目标随机规划模型[J]. 系统工程理论与实践, 2013, 33(1): 159-166.
[9] 蔡玫, 罗倩, 朱莉,等. 面向应急物资调度的一种模糊规划模型[J]. 系统管理学报, 2013, 22(4): 487-493.
[10] 刘晔, 姜国刚. 决策者风险态度对应急物资调度影响研究[J]. 中国安全科学学报, 2014, 24(8): 170-176.
[11] 宋晓宇, 王建国, 常春光. 基于需求紧迫度的非线性连续消耗应急调度模型与算法[J]. 信息与控制, 2014, 43(6): 735-743.
[12] 张玲, 陈涛, 黄钧. 基于最小最大后悔值的应急救灾网络构建鲁棒优化模型与算法[J]. 中国管理科学, 2014, 22(7): 131-139.
[13] 陈涛, 黄钧, 朱建明. 基于信息更新的两阶段鲁棒-随机优化调配模型研究[J]. 中国管理科学, 2015, 23(10): 67-77.
[14] 阮俊虎, 王旭坪, 杨挺. 大规模灾害中基于聚类的医疗物资联合运送优化[J]. 中国管理科学, 2014, 22(10): 80-89.
[15] 许胜铭, 景国勋. 煤矿瓦斯爆炸事故的应急救援物资调度模型研究[J]. 安全与环境学报, 2015, 15(5): 104-107.
[16] Dorigo M, Maniezzo V, Colorni A. Ant system: Optimization by a colony of cooperative agents[J]. IEEE Transactions on SMC, 1996, 26(1): 28-41.
[17] 余谦, 王先甲. 基于粒子群优化求解纳什均衡的演化算法[J]. 武汉大学学报(理学版), 2006, 52(1): 25-29.
[18] Mladenovic N, Hansen P. Variable neighbourhood search[J]. Computers and Operations Research, 1997, 24(11): 1097-1100.
[19] Hansen P, Mladenovic N, Peter J A. Variable neighbourhood search: Methods and applications[J]. Annals of Operations Research, 2010, 175(1): 367-407.
[20] 曹正洋, 许维胜, 徐志宇. 开放式两级车辆路径问题建模与多起始点变邻域下降法求解[J]. 计算机科学, 2014, 41(10): 232-237.
[21] 陈士俊, 孙永广, 吴宗鑫. 一种求解NASH均衡解的遗传算法[J]. 系统工程, 2001, 19(5): 67-70.
[22] 刘维. 精通Matlab与C/C++混合程序设计(第二版)[M]. 北京:北京航空航天大学出版社, 2008.
