Sustainable Spatial Land Use Optimization through Non-Dominated Sorting Genetic Algorithm-II (NSGA-II): (Case Study: Baboldasht District of Isfahan)

A heuristic method named as non-dominated sorting genetic algorithm version two (NSGA-II) is developed for multi-objective land use allocation based on the concept of sustainable development which is the predominant notion of land use planning. Numerous plans are generated and optimized by NSGA-II according to land use allocation objectives: maximizing compactness, maximizing floor area ratio, maximizing compatibility, maximizing economic benefit and maximizing mix use. These objectives and constraints are formulated and combined through weighted sum method. This paper moves the previous studies forward in several aspects: 1) application of non-linear objective functions which represent the complexity of real word better than linear functions, 2) modification of NSGA-II operators to fit it for application in urban land use planning framework, and 3) adding density related objective functions which represent the concept of sustainable development more comprehensive. Application of NSGA-II in land use allocation of Baboldasht district, demonstrates effectiveness and the potential of this algorithm in development of planning support system through representation of optimal solutions with different preferences.

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