摘要
针对目前人群行为仿真中多目标,有约束的组合优化问题,提出了一种改进遗传算法在人群行为仿真的应用方案。通过设定特殊的数据结构、仿真过程中的各种约束规则、遗传算法中的基因编码、适应度评价函数实现了人群行为仿真。仿真实验验证了该算法可以大大减少搜索空间,并能使结果达到最优。
For the combinatorial optimization problem of crowd behavior simulation multi-objective and constrained, proposed a improved genetic algorithm in the application of group behavior simulation. By setting the special data structure to simulate the process of a variety of constraint rules, genetic encoding of genetic algorithm, fittness evaluation function implement of crowd behavior simulation. Simulation experiment verified that the method can greatly reduce the search space, and enables optimal results.
出处
《电子设计工程》
2013年第13期25-27,共3页
Electronic Design Engineering
基金
河南省基础与前沿技术研究计划项目(122300410393)
关键词
遗传算法
数据结构
适应度评价函数
人群行为仿真
genetic algorithm
data structure
fitness evaluation function
crowd behavior simulation
