带策略约束的区间数双矩阵博弈的双线性规划求解方法

展开
  • 1. 福州大学经济与管理学院, 福州 350108;
    2. 电子科技大学经济与管理学院, 成都 611731

收稿日期: 2018-08-11

  网络出版日期: 2019-09-09

基金资助

国家自然科学基金重点项目(No.71231003)

Bilinear programming method to solve interval bimatrix games with constrained strategy

Expand
  • 1. School of Economics and Management, Fuzhou University, Fuzhou 350108, China;
    2. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China

Received date: 2018-08-11

  Online published: 2019-09-09

摘要

传统区间数双矩阵博弈理论研究局中人支付值为区间数的策略选择问题,但没有考虑局中人策略选择可能受到各种约束.创建一种求解局中人策略选择受约束且支付值为区间数的双矩阵博弈(简称带策略约束的区间数双矩阵博弈)的简单、有效的双线性规划求解方法.首先,将局中人的博弈支付看作支付值区间中数值的函数.通过证明这种函数具有单调性,据此利用支付值区间的上、下界,构造了一对辅助双线性规划模型,可分别用于显式地计算任意带策略约束的区间数双矩阵博弈中局中人区间数博弈支付的上、下界及其相应的最优策略.最后,利用考虑策略约束条件下企业和政府针对发展低碳经济策略问题的算例,通过比较其与不考虑策略约束情形下的结果,说明了提出的模型和方法的有效性、优越性及可应用性.

本文引用格式

肖燕, 李登峰 . 带策略约束的区间数双矩阵博弈的双线性规划求解方法[J]. 运筹学学报, 2019 , 23(4) : 59 -70 . DOI: 10.15960/j.cnki.issn.1007-6093.2019.04.005

Abstract

Traditional interval bimatrix game theory is used to study players. strategy selection problems with interval payoff; however, such a theory does not consider players.strategy selection which may be subjected to various constraints. The purpose of this paper is to develop a simple and an effective bilinear programming method to solve the bimatrix game in which players. strategy selection is constrained, and the payoffs are intervals, which is called the interval bimatrix game with constrained strategy. Firstly, the values of players are regarded as functions of the values in the payoff intervals, which are of monotonicity. Therefore, we construct a pair of auxiliary bilinear programming models, which are used to explicitly compute the upper and lower bounds of the interval values of players in any interval bimatrix game by respectively using the lower and upper bounds of the payoff intervals and corresponding optimal strategies. Finally, based on a case of enterprise and government in developing a low-carbon economy in the situation that their strategies are constrained. The effectiveness, advantages, and applicability of the models and methods proposed in this paper are illustrated by comparing these results with those without considering strategic constraints.

参考文献

[1] Owen G. Game Theory[M]. New York:Academic Press, 1982.
[2] Holler M J. Game theory with applications to economics by James W. Friedman[J]. Journal of Economic Education, 1986, 23:89-92.
[3] Saloner G. Modeling, game theory, and strategic management[J]. Strategic Management Journal, 1991, 12:119-136.
[4] Qiao-Lun G U, Gao T G, Shi L S. Price decision analysis for reverse supply chain based on game theory[J]. Systems Engineering-theory and Practice, 2005, 25:20-25.
[5] Zhang H, Shu L. Generalized interval-valued fuzzy rough set and its application in decision making[J]. International Journal of Fuzzy Systems, 2015, 17:279-291.
[6] Mottaghi A, Ezzati R, Khorram E. A new method for solving fuzzy linear programming problems based on the fuzzy linear complementary problem[J]. International Journal of Fuzzy Systems, 2015, 17:236-245.
[7] Moore R E. Methods and Applications of Interval Analysis[M]. DBLP, 1979.
[8] Hladík M. Multiparametric linear programming:Support set and optimal partition invariancy[J]. European Journal of Operational Research, 2010, 202:25-31.
[9] Hladík M. Interval valued bimatrix games[J]. Kybernetika-Praha-, 2010, 3:435-446.
[10] Vijay V, Chandra S, Bector C R. Matrix games with fuzzy goals and fuzzy payoffs[J]. Omega, 2005, 33:425-429.
[11] Larbani M. Solving bimatrix games with fuzzy payoffs by introducing nature as a third player[J]. Fuzzy Sets and Systems, 2009, 160:657-666.
[12] Nan J X, Zhang M J, Li D F. Intuitionistic fuzzy programming models for matrix games with payoffs of trapezoidal intuitionistic fuzzy numbers[J]. International Journal of Fuzzy Systems, 2014, 16:444-456.
[13] Zadeh L A. Fuzzy sets[J]. Information and Control, 1965, 8:338-353.
[14] Moore R E. Methods and applications of interval analysis[J]. Siam Studies in Applied Mathematics Philadelphia, 1979, 2:33-57.
[15] Sayadi M K, Heydari M, Shahanaghi K. Extension of VIKOR method for decision making problem with interval numbers[J]. Applied Mathematical Modelling, 2009, 33:2257-2262.
[16] Jahanshahloo G R, Lotfi F H, Davoodi A R. Extension of TOPSIS for decision-making problems with interval data:Interval efficiency[J]. Mathematical & Computer Modelling, 2009, 49:1137-1142.
[17] Ramík J. Inequality relation between fuzzy numbers and its use in fuzzy optimization[J]. Fuzzy Sets and Systems, 1985, 16:123-138.
[18] Kunsch P L, Kavathatzopoulos I, Rauschmayer F. Modelling complex ethical decision problems with operations research[J]. Omega, 2009, 37:1100-1108.
[19] Wenstp F, Koppang H. On operations research and value conflicts[J]. Omega, 2009, 37:1109-1120.
[20] Hua Z, Zhang X, Xu X. Product design strategies in a manufacturer-retailer distribution channel[J]. Omega, 2011, 39:23-32.
[21] Liu Z F, Huang G H, Nie X H, et al. Dual-interval linear programming model and its application to solid waste management planning[J]. Environmental Engineering Science, 2009, 26:1033-1045.
[22] Sengupta A, Pal T K. On comparing interval numbers[J]. European Journal of Operational Research, 2000, 127:28-43.
[23] Sengupta A, Pal T K, Chakraborty D. Interpretation of inequality constraints involving interval coefficients and a solution to interval linear programming[J]. Fuzzy Sets and Systems, 2001, 119:129-138.
[24] Ben-Israel A, Robers P D. A decomposition method for interval linear programming[J]. Linear Algebra and Its Applications, 1970, 3:383-405.
[25] Robers P D, Benisrael A. Interval programming. New approach to linear programming with applications to chemical engineering problems[J]. Industrial and Engineering Chemistry Process Design and Development, 1968, 8:496-501.
[26] Li D F. Notes on "Linear programming technique to solve two-person matrix games with inteval pay-offs"[J]. Asia-Pacific Journal of Operational Research, 2011, 28:705-737.
[27] Li D F, Nan J X, Zhang M J. Interval programming models for matrix games with interval payoffs[J]. Optimization Methods and Software, 2012, 27:1-16.
[28] Fei W. Interval-valued bimatrix game method for engineering project management[J]. International Journal of Fuzzy System Applications, 2015,4:1-12.
[29] Firouzbakht K, Noubir G, Salehi M. Linearly constrained bimatrix games in wireless communications[J]. IEEE Transactions on Communications, 2016, 64:429-440.
[30] Nash J. Non-cooperative games[J]. Annals of Mathematics, 1951, 54:286-295.
文章导航

/