Optimization of multi-objective land use model with genetic algorithm


  • Hasan Mutlu Urban Planner (M.Sc.)

    Hasan MUTLU has been working as a software specialist for 14 years for Netcad which has been developing GIS and CAD applications. He develops CAD and GIS based software related to civil engineering and city planning. He specializes in developing optimization algorithms on these fields. He took part in various Planning and Research Projects (İstanbul Metropolitan Area Plan (2005) – İstanbul Historical Peninsula Plan(2001)) as a consultant. He has academic articles in international/national journals and several conference papers in international conferences.




spatial optimization, genetic algorithm, multi objective land use planning


The first task of the city planner is to effectively locate integrated land use types for various objectives. The Multi Objective Land Use Planning Model developed to achieve this goal, aims to maximize land value and minimize the transportation. The genetic algorithm method developed to find the optimum layout according to the Multi-Objective Land Use Planning Model has been explained, the success and performance of the process has been tested with artificial data, and its usability in real problems has been examined. According to the results of the study, using this method, it is revealed that layout plans that are very close to the maximum efficiency value can be found within 1 day in cities with a population of up to 1,000,000, within 1 week in cities up to 5,000,000, and within 1.5 months in cities close to 16,000,000. By examining the results, the deficiencies of this method are determined and the suggestions for improvement of this method are stated. The problem chosen in this study is a problem that most city planners have to solve and the developed application has been opened to the use of other experts. This makes this work unique as it allows planning experts who are incapable of developing such methods to experiment.


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How to Cite

Mutlu, H. (2020). Optimization of multi-objective land use model with genetic algorithm. Journal of Design for Resilience in Architecture and Planning, 1(1), 15–32. https://doi.org/10.47818/DRArch.2020.v1i1002



Research Articles