基因表达式编程的多目标空间选址优化

Gene Expression Programming Algorithm for Multi-Objective Spatial Siting Optimization

提出了基因表达式编程算法(GEP)的Pareto多目标空间选址模型,成功求解了Bohachevsky函数及Shubert多峰函数模拟空间分布的选址问题。将此方法应用于广州市公共设施的空间优化选址,取得了较好的结果。

This paper describes an improved approach based on the gene expression programming（GEP）algorithm,with which the multi-objective site selection problems can be resolved.The validity of this approach in finding optimal or near-optimal solutions is demonstrated by using Bohachevsky test function and Shubert test function whose optimal solutions are known.The application of the proposed method in the allocation of hypothetical facilities in Guangzhou City shows preferable result.