Abstract：
Our world has had difficulty meeting humans\' needs in recent years. To ensure that the world can sustain its inhabitability and self-sufficiency in terms of natural resources, it is required to make the total amount of biocapacity areas equal to or higher than the ecological footprint. An analytical study has been carried out to remedy the biocapacity deficit by utilizing this information for Turkey and then these areas are optimized with heuristic optimization techniques. As a result, Artificial Bee Colony provides better objective function results (fewer errors) compared to Particle Swarm Optimization and Global Optimization Method Based on Clustering and Parabolic Approximation in terms of minimum, maximum, average value, and standard deviation. The rates of change according to the current situation of the biocapacity areas in 2016 are 277.97 %, 30.28 %, -29.28 %, 14.97 %, and -44.85 % for cropland, grazing land, forestland, fishing grounds, and built-up land, respectively. Depending on the population growth, these rates should additionally change by 83.24 %, -0.69 %, 3.97 %, 6.22 %, and -14.24 % respectively in 2050. The developed model can be used in industry or within the frame of government development policy and thus the balance between ecological footprint and biocapacity can be kept under control.
摘要：
近年来，我们的世界很难满足人类的需求。为了确保世界能够在自然资源方面维持其可居住性和自给自足，要求生物承载力面积总量等于或高于生态足迹。已经进行了一项分析研究，通过利用土耳其的这些信息来弥补生物容量不足，然后使用启发式优化技术对这些区域进行优化。因此,人工蜂群在最小值方面比粒子群优化和基于聚类和抛物线逼近的全局优化方法提供了更好的目标函数结果(误差更少),最大值,平均值,和标准偏差。根据2016年生物净度区现状，变化率为277.97%，30.28%，-29.28%，14.97%,农田为-44.85%，放牧的土地,林地,渔场,和建成用地。根据人口的增长,这些比率应另外变化83.24%，-0.69%，3.97%,6.22%，和2050年分别为-14.24%。开发的模型可用于工业或政府发展政策框架内，因此可以控制生态足迹和生物承载力之间的平衡。
