Abstract. One of the most significant challenges in land use planning and management is how to optimize the use of available arable lands based on their limitations for natural resource conservation. In this regard and due to the interaction of numerous conflicting objectives, multiobjective meta-heuristic algorithms are introduced for solving such types of issues. This research aims to analyze the sensitivity of NSGA-II parameters and introduces a model for land use change optimization considering some constraints. Three objective functions were established as economic benefits (F1), adaptability of land use (F2), and land conversion difficulty (F3) towards maximization of economic benefits and the adaptability of land use with its neighbors while minimizing land conversion difficulty (LCD). To prepare the land use map, Landsat8(OLI) images were classified using maximum likelihood classification (MLC) algorithm with an accuracy of about 93 percent. To generate a scheme and pairwise comparison for each objective function, AHP multi-criteria decision-making method was used. Then, the coefficient of NSGA-II operators was evaluated by trial and error approach to reach and select their optimal values. The gained optimal values for the objective functions result in an optimal plan for land use change. The evaluation of the convergence and stability of the algorithm proves the acceptability of achieved results. Based on different scenarios, increase the economic benefits are up to 99, 69, and 63 percent. Consequently, the introduced approach may be applicable for official managers to overcome multi-objective problems toward a sustainable development policy for environmental conservation on local and national scales.
Sadidi et al. (Fri,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: