title: An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas.
abstract: China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC)-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining "replace" and "alter" operations, and the third is a "swap" strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China), and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing) was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures.
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Shao
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China.
authors.forename: Lina
authors.initials: L
authors.lastname: Yang
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Peng
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China.
authors.forename: Tianhe
authors.initials: T
authors.lastname: Chi
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Xiaomeng
authors.initials: X
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D002681:China; D003198:Computer Simulation; D003247:Conservation of Natural Resources; D004463:Ecology