摘要
为了解决多目标的优化问题，提出了变动临近区域遗传算法。算法在解决设施布置问题时，改进了质化研究和量化研究中的一些不足。仿真结果表明，与传统的的NPGA、VEGA遗传算法相比较，该算法在最终解个数、算法的稳定性、染色体的均匀程度等评价指标上为最优。
In order to solve multi -objective optimization problems, this paper presents neighboring change genetic algorithm. The algorithm would improve some deficiencies in the qualitative and quantitative research while solving facility layout problems. Compared with traditional NPGA and VEGA , simulation results show that algorithm performance is most optimal evaluation index in the number of final solution, stability and chromosome uniformity.
出处
《陕西交通职业技术学院学报》
2012年第4期47-50,共4页
Journal of Shaanxi College of Communication Technology
基金
项目基金：中央高校基本科研业务费专项资金（CHD2010ZY012）
