Designing a Multi-objective Optimization Model of Land Use, based on Genetic Algorithms (Case study: Kerman- Rodbar Watershed)

With the increase in population and consequent increasing needs of society, land use planning is of particular importance. Land use planningdue to being involved with several conflicting aims, multi- objective evolutionary algorithm would be a useful tool to solve land use planning. But use of these algorithms should be examined according to the type of issues. In the study, addition to introducing a model to optimize land use, effective solution for the application of multi- objective genetic algorithm on a variety of problems related to land use planning was presented. In order to land uses optimization in the study, the algorithm NSGA-II was use in the model. Output of the model might be introduced patterns for reduction of erosion to an acceptable level and enhancing the economic benefits. This will be skillfully carried out while the land use adaptation is in the highest level and land use changes are easy with high level of continuity.An innovative operator which producing the initial population and an innovative operator with an appropriate Crossover of land use planning issues were developed.The developed model in the study was implemented in Kerman-Rodbar watershed. Evaluation results show that the model is able to suggest patterns to land use planning that reduce erosion about 30 to 35%. While the economic benefits of the changes will be about 40 to 50 %. Furthermore all models have a high consistency and low difficulty to change. These operators have had a significant impact on problem solving. Keywords: Multi- objective optimization, NSGA-II algorithm, Innovative Operators, Land use planning, Ecological potentiality