Adaptive genetic algorithm for multi-objective sustainable land use planning

Abstract

Land use and land cover change (LUCC) is a complex process related to the interactions among natural, social and economic systems on different temporal and spatial scales. How to settle land resource allocation problem (RAP), especially the sustainable development of land use with more than one objective and constraint, has been a challenging task for decision makers and planners for a long time. Considering economy, environment and spatial layout, this paper proposes an optimization model for sustainable development of land use. Given the multi-objective nature of multi-objective redundancy allocation problem (MORAP), an adaptive genetic algorithm (GA) is developed to solve the problem of constrained land use optimization via maxmin fitness evaluation and robust genetic operations. With the support of geographical information system (GIS), a case study is carried out for land-use optimization for Changqing district. The experimental results demonstrate the efficacy of the proposed approach.