Application of multi-objective game-theory model for the purpose of land use optimization of Zemkan basin

This study was carried out with the aim of feasibility evaluation of the application of multi-objective game-theory model for settling balance between economic and environmental concerns in land use optimization as well as to facilitate the respective decision-makings in Zemkan basin, located in the west of Kermanshah Province. The bi-objectives of multi-objective game-theory model are minimizing the destructive effects on the environment (less erosion and sediments) and maximizing the economical incomes resulted from different land uses (more net present value). The IRS-P6 Satellite images were used for recognition of different land uses and the areas of these land uses were determined using GIS tools. In this study, the environmentalists (player 1) and Zemkan basin users (player 2) were selected as environmental and economical players, respectively. In this study, an integration of game theory, multi-objective optimization and geographic information system was used in land use optimization of Zemkan basin in order to set balance between economic development and environmental effects. The results of multi-objective game-theory model indicated that after several rounds of bargaining and moderating the objectives between players, Nash equilibrium would be resulted. Within Nash equilibrium limits, the mean of erosion and sediment ranges from 4296 to 4300 thousands m3 per year and net present value, also ranges from 47050 to 47068 million Rials for economic player. Comparing with Pareto optimality, which is the result of classical multi- objective model, Nash equilibrium offered more satisfactory solutions based on decision makers’ priorities. The results also suggest that the game theory model can be applied in many other issues concerning environmental management. The future researches may concentrate on developing a third objective like social concerns so that three-objective games would be applied instead of bi-objective ones.