摘要
基于蚁群优化算法,求解含有未知内热源位置的导热逆问题.通过分析计算表明:信息素启发因子、能见度启发因子、信息素挥发率等蚁群参数对蚁群选择路径以及路径上信息素浓度更新有直接影响,其取值最终会影响求解结果的准确性及收敛速度.在计算过程中,路径上的信息素浓度不断改变,蚂蚁选择路径也趋于集中,采用定值蚁群参数不能满足在整个计算过程中都具有良好的性能,为此提出了动态参数蚁群算法,并根据计算分析结果确定蚁群参数值随全局循环次数而变的动态函数.计算结果证明,采用动态参数蚁群算法能有效提高求解反问题的质量及收敛速度.
To solve the inverse heat conduction problem with unknown location of heat source,an ant colony algorithm with dynamic parameters,being a probabilistic algorithm,was proposed.The analysis and calculation show that the pheromone inspiration factor,visibility inspiration factor, pheromone evaporation rate and other ant colony parameters directly impact the way of updating the pheromone concentrations.Their values ultimately affect the accuracy of the results and the convergence rate.In the calculation process,the pheromone concentrations on the path will be constantly changing,and the ants will tend to select a concentrated path.The ant colony optimization algorithm with constant ant colony parameter values can’t guarantee to have good performance in the entire calculation process.Therefore,the ant colony algorithm with dynamic parameters was proposed,and the dynamic function of ant colony parameter values which changes with the times of global cycles was constructed according to the calculation results of the analysis. The results show that the proposed method is an accurate and efficient method to seek the location of heat source in inverse heat conduction problems.
出处
《上海理工大学学报》
CAS
北大核心
2016年第2期126-132,共7页
Journal of University of Shanghai For Science and Technology
基金
国家自然科学基金资助项目(51176126)
关键词
导热逆问题
热源
动态参数
蚁群算法
inverse heat conduction problem
heat source
dynamic parameter
ant colony algorithm
