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随着现代社会经济的飞速发展
各个经济系统的联系不断加强
如何实现各个系统的利益最大化和成本最小化
成为人们日益关注的焦点.针对该类问题
研究了一类多人合作多目标交叉规划.首先给出了多人合作交叉多目标规划的模型
从该模型出发给出了求解多人交叉多目标规划的一种算法:对交叉规划问题中的每个子目标函数求解
将交叉规划问题转化为非线性规划问题
通过引入罚因子
用外罚函数法求出非线性规划的最优解.该解也是多人多目标交叉规划问题的非劣解
从该非劣解出发进行搜索
寻找最优解.最后通过算例验证了算法的可行性和有效性.
With the rapid development of the modern society and economy
every economic system is related among them.How to achieve to maximize interest and minimize cost has been paid more and more attention.First
The model of many-person multi-objective interaction programming was established.Then a corresponding algorithm of many-person multi-objective interaction programming was given.The previous model was converted into a nonlinear programming problem by solving every sub-objective function in interaction programming.The nonlinear programming problem was turned into unconstrained optimization problem by the use of exterior penalty function method.The solution was also non-inferior solution of the many-person multi-objective interaction programming.Optimal solution could be found via search feasible descent direction.Finally
feasibility and validity of the algorithm were verified.
刘家壮.交叉规划问题[J].经济数学,1998,15(1):11-16.Liu Jiazhuang.Interactive mathematics programmingproblems[J].Mathematics in Economics,1998,15(1):11-16.(in Chinese)
孟志青,李荣生.两人交叉决策联合最优解的存在性[J].运筹学学报,1999,3(1):52-55.Meng Zhiqing,Li Rongsheng.Existence of allient op-timal solution for two-man’s interactive mathematicalprogramming problems[J].Operations ResearchTransactions,1999,3(1):52-55.(in Chinese)
Meng Zhiqing,Hu Qiying,Dang Chuangyin.A math-ematical programming model for the coexistence ofcompetitions problems[J].Journal of System andComplexity,2005,18(4):556-563.
Meng Zhiqing,Hu Qiying,Jiang Min,et al.Interac-tional programming model for the coexistence of com-petitions and cooperations problems[J].InteractionalJournal of Management Science and Engineering Man-agement,2007(2):138-146.
Meng Zhiqing,Hu Qiying,Dang Chuangyin.A penal-ty function algorithm with objective parameters fornonlinear mathematical programming[J].Journal ofIndustrial and Management Optimization,2009,5(3):585-601.
徐新生,孙建武.两人交叉规划问题的最优整体差解[J].山东大学学报(理学版),2008,43(12):52-55.Xu Xinsheng,Sun Jianwu.An optimal integral differ-ential solution for a two-person interaction program-ming problem[J].Journal of Shandong University(Natural Science),2008,43(12):52-55.(in Chinese)
孟志青,胡奇英.一类两人合作交叉规划的s-最优联合解[J].系统工程与电子技术,2002,24(8):17-20.Meng Zhiqing,Hu Qiying.s-Optimal joint solutionsfor two-person cooperative interaction programming[J].Systems Engineering and Electronics,2002,24(8):17-20.(in Chinese)
孟志青,李坤,蒋敏.两人多目标交叉规划的s-最优联合解[J].浙江工业大学学报,2011,39(4):355.Meng Zhiqing,Li Kun,Jiang Min.s-Optimal joint so-lutions for two-person multi-objective interaction pro-gramming[J].Journal of Zhejaing University of Tech-nology,2011,39(4):355.(in Chinese)
何坚勇.最优化方法[M].北京:清华大学出版社,2007.
张丽萍.基于交叉规划的订货策略优化模型及其求解算法[J].北京建筑工程学院学报,2012,28(2):64.Zhang Liping.Optimal model and its solution algo-rithm for ordering policy based on interaction pro-grammig[J].Journal of Beijing University of CivilEngineering and Architecture,2012,28(2):64.(inChinese)
张丽萍.基于空间价格平衡的订货策略交叉规划模型及算法研究[J].北京建筑工程学院学报,2010,26(2):65-72.Zhang Liping.Optimal model and its solution algo-rithms for ordering policy based on interaction programming and spatial pricing equilibrium[J].Journalof Beijing University of Civil Engineering and Archi-tecture,2010,26(2):65-72.(in Chinese)
徐新生.求解交叉规划问题的几个公平公理[J].滨州学院学报,2009,25(3):39.Xu Xinsheng.Some fair axioms for solving interac-tion programming problem[J].J.of Binzhou Univer-sity,2009,25(3):39.(in Chinese)
徐新生.求解交叉规划模型的一类联合均衡方法[J].山东大学学报(理学版),2009,44(6):51-55.Xu Xinsheng.A joint equilibrium method for solving interaction programming models[J].Journal of Shan-dong University(Natural Science),2009,44(6):51-55.(in Chinese)
马建华.线性交叉规划的等价形式[J].运筹学学报,2006,10(3):121-125.Ma Jianhua.The equivalence programming of linear interaction programming[J].Operations Research Transaction,2006,10(3):121-125.(in Chinese)
李坤.基于交叉规划理论的两级供应链定价问题研究[D].杭州:浙江工业大学,2010.
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