Generalized DEA model and the convex cone constrained game

This study extends the research on relating the data envelopment analysis (DEA) with the game theory context. We propose a generalized model for the two-person zero-sum finite game with closed convex cone constraints. We prove that the strategy of the closed convex cone constrained two-person zero-sum finite game is equivalent to the solution of the corresponding cone constrained programming problem. We show the existence of an optimal strategy of closed convex cone constrained two-person zero-sum finite game. As a special case of this, we give the optimal strategy of a polyhedral constrained game. In this case, the corresponding dual programming problems are a pair of linear dual programming problems. We then build up the connection between the proposed convex cone constrained game model and the generalized DEA model. With this relationship, a more robust correspondence between game family and the DEA family is established.