Simulating multi-objective land use optimization allocation using Multi-agent system-A case study in Changsha, China

Authored by Honghui Zhang, Xiaobin Jin, Yinkang Zhou, Bangrong Shu, Yongnian Zeng, Xuhong Yang

Date Published: 2016

DOI: 10.1016/j.ecolmodel.2015.10.017

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Achieving multi-objective land use optimization allocation (MOLUOA) for sustainable development is an important issue in land use. In consideration of the multi-dimensional characteristics of MOLUOA in terms of quantity, space, and time, and under the constraints of maximizing economic, ecological, and social benefits of land use, a MOLUOA model is developed in this study by integrating multi-agent system with particle swarm optimization. The MOLUOA model is applied to the simulation of land use optimization allocation in Changsha, a typical city located in central China. Simulation results show that the MOLUOA model can achieve multi-objective land use optimization allocation in terms of quantity, space, and time. The model can provide decision-making support for generating land use alternatives to achieve sustainable land use. (C) 2015 Elsevier B.V. All rights reserved.

Tags

Genetic algorithm Spatial optimization Particle swarm optimization Agent-based models Urban-development Coupled human Cover change Cellular-automata model Dynamics model Large areas