scholarly journals Interval Fuzzy Linear Programming Models to Solve Interval-valued Fuzzy Zero-Sum Games

2015 ◽  
Author(s):  
Stephanie Loi Briao ◽  
Gracaliz Pereira Dimuro ◽  
Catia Maria Dos Santos Machado
Keyword(s):  
Linear Programming ◽  
Fuzzy Linear Programming ◽  
Programming Models ◽  
Zero Sum Games ◽  
Zero Sum ◽  
Interval Valued

Vector Valued Non Zero Sum Games and Non Linear Programming

OPSEARCH ◽  
1997 ◽  
Vol 34 (3) ◽  
pp. 180-185 ◽  
Author(s):  
M. V. Durga Prasad ◽  
P. C. Sreenivas
Keyword(s):  
Linear Programming ◽  
Non Linear Programming ◽  
Zero Sum Games ◽  
Non Linear ◽  
Zero Sum ◽  
Vector Valued

Solving Two-Person Zero-Sum Game by Matlab

2011 ◽  
Vol 50-51 ◽  
pp. 262-265 ◽  
Author(s):  
Yan Mei Yang ◽  
Yan Guo ◽  
Li Chao Feng ◽  
Jian Yong Di
Keyword(s):  
Game Theory ◽  
Linear Programming ◽  
Special Class ◽  
The Other ◽  
Matrix Game ◽  
Matlab Software ◽  
Zero Sum Games ◽  
Programming Techniques ◽  
Zero Sum

In this article we present an overview on two-person zero-sum games, which play a central role in the development of the theory of games. Two-person zero-sum games is a special class of game theory in which one player wins what the other player loses with only two players. It is difficult to solve 2-person matrix game with the order m×n(m≥3,n≥3). The aim of the article is to determine the method on how to solve a 2-person matrix game by linear programming function linprog() in matlab. With linear programming techniques in the Matlab software, we present effective method for solving large zero-sum games problems.

Finding compromise solutions for fully fuzzy multi-olbjective linear programming problems by using game theory approach

2021 ◽  
pp. 1-11
Author(s):  
Gizem Temelcan ◽  
Hale Gonce Kocken ◽  
Inci Albayrak
Keyword(s):  
Game Theory ◽  
Linear Programming ◽  
Fuzzy Linear Programming ◽  
Theory Approach ◽  
Compromise Solution ◽  
Objective Functions ◽  
Multiobjective Linear Programming ◽  
Trade Off ◽  
Linear Programming Problems ◽  
Zero Sum

Solving multiobjective linear programming (MOLP) problems and fully fuzzy multi-objective linear programming (FFMOLP) problems involves the trade-off process among several objectives. A new algorithm extended where FFMOLP problems are solved using a 2-player zero-sum game approach to deal with this case. Firstly, The FFMOLP problem is separated into a certain number of fully fuzzy linear programming (FFLP) problems and each is solved by applying any method. After forming a ratio matrix, a game theory approach is applied for finding the weights of objective functions and a weighted LP problem is constructed by these weights. Solving the weighted LP problem, a fuzzy compromise solution of the FFMOLP problem is found. Constructing different ratio matrices, it is also possible to obtain more than one compromise solution to be offered to the decision-maker(s). Some examples are given to show the applicability of the algorithm.

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