Urban Land-Use Allocation By A Cell-based Multi-Objective Optimization Algorithm

Allocating urban land-uses to land-units with regard to different criteria and constraints is considered as a spatial multi-objective problem. Generating various urban land-use layouts with respect to defined objectives for urban land-use allocation can support urban planners in confirming appropriate layouts. Hence, in this research, a multi-objective optimization algorithm based on grid is proposed to generate well-distributed solutions in objective space. In order to preserve diversity in Pareto front approximation, a grid is defined in objective space. The cells of this grid cluster the solutions and determine the suitable solutions for next generation in optimization process. The land-uses of region 1 of the district 7 of Tehran is used to assess the efficiency of the algorithm in optimizing urban land-use allocation. The results of the proposed algorithm are compared with the results of Non-dominated Sorting Genetic Algorithm II and III (NSGA-II and NSGA-III). Comparing the results indicate that the proposed algorithm acts better than NSGA-II and NSGA-III in preserving diversity and improving the convergence of the solutions in Pareto front.