改进粒子群进化计算的公路工程造价评估算法

Highway Engineering Cost Assessment Algorithms Based on Improved Particle Swarm Evolution Calculation

为了解决公路工程造价评估算法中的计算速度和精度问题,提出了改进粒子群进化计算的公路工程造价评估算法。该算法首先将公路工程造价最优评估方案问题转化为多目标参数约束条件下的候选工程项目造价方案动态寻优问题;然后利用改进粒子群算法对公路工程造价候选方案进行粒子映射,依据粒子粒距聚类度和粒子信息熵对粒子权值进行修正,再计算粒子的适应度值,对粒子的局部最优解和全局最优解进行更新;最后利用粒子速度和位置更新策略对动态进行迭代优化。仿真对比实验证明,该算法具有较好的收敛速度,且收敛值更优,评估方案的计算精度有显著得提升。

In order to solve the highway engineering cost evaluation algorithm of calculating speed and accuracy problem, puts forward the improved particle swarm evolution calculation of the highway engineering cost evaluation algorithm. In this algorithm, the first highway engineering cost will be the optimal evaluation scheme into which is objective parameter constraint conditions the candidate project cost plan dynamic optimization problems; Then the improved particle swarm optimization （pso） algorithm for highway engineering cost candidate schemes particle mapping, on the basis of the particle grain distance clustering degree and particle information entropy weights to particle modified, and then computing the particle＇s fitness value, the particle of the local optimal solution and the global optimal solution to update; Finally, using the particle velocity and position update strategies on dynamic iterative optimization. Simulation experiments show that this algorithm has good convergence speed and convergence value more optimal, evaluate the calculation precision of the scheme has markedly improved.