Generating Alternative Land‐use Allocation for Mixed Use Areas: Multi‐Objective Optimization Approach

Current research is carried out with an intention to present an optimization approach for the urban land-use allocation problem by generating Pareto optimum solutions considering two objectives-maximizing compatibility among adjacent space uses of a study area without compromising the area's total land price and maximizing the price of plot of each individual owner. Considering the non-linear characteristics of the objective functions, a multi-objective evolutionary algorithm approach called Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to obtain Pareto optimal land-use allocation subject to different set of constraints. The objective functions are tested over a case study area of Dhaka, Bangladesh. The resulting NSGA-II model produces 24 Pareto optimal solutions of land-use allocation, allowing tradeoff between maximizing compatibility and land price from one solution to other. This research also expresses the potential of the model to aid the policymakers and city planners of development authorities by providing alternative land-use plans, and thereby predicting the consequences of any plan before practical application.