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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Developing an integrated land allocation model based on linear programming and game theory.

Farzam Hasti1, Abdolrassoul Salmanmahiny2, Haydar Rouhi2

  • 1Department of Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. farzam.hasti@gmail.com.

Environmental Monitoring and Assessment
|March 21, 2023
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Summary

This study integrates game theory and linear programming for optimal land use planning. It successfully resolved stakeholder conflicts, reaching a Nash Equilibrium for balanced ecological, economic, and social goals.

Keywords:
Game theoryGeospatial information system (GIS)Land allocationLinear programming

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Area of Science:

  • Environmental Science
  • Spatial Planning
  • Game Theory

Background:

  • Land use configuration results from multi-objective optimization involving ecological, economic, and social factors.
  • Stakeholder coordination is crucial for successful spatial land use optimization.
  • Game theory offers a framework to model stakeholder interactions in land use planning.

Purpose of the Study:

  • To develop an integrated model combining linear programming and game theory for spatial land use allocation.
  • To address and resolve conflicts among diverse stakeholders in land use planning.
  • To achieve an optimal land use configuration acceptable to all parties.

Main Methods:

  • An integrated model using linear programming and game theory was designed.
  • Multi-objective land allocation (MOLA) and linear programming were employed for optimal land use allocation.
  • A game algorithm was utilized to select constraints ensuring stakeholder acceptability.

Main Results:

  • The integrated model successfully modeled interactions between environmental and land development stakeholders.
  • The decision-making process reached the desired Nash Equilibrium by the third round of the game.
  • Stakeholder conflicts were effectively resolved, leading to an optimized land use allocation.

Conclusions:

  • The integrated linear programming and game theory model provides an effective approach for spatial land use optimization.
  • Achieving Nash Equilibrium through game theory facilitates conflict resolution among stakeholders.
  • The presented solution, localized in a GIS environment, offers practical applications for land use planning.