基于改进蚁群算法在工程项目工期——成本优化问题研究

A Time-cost Optimization Research for the Project Based on Improved Ant Colony Algorithm

为了解决蚁群算法容易陷入局部最优,求解容易出现停滞现象,本文从转移概率和信息素挥发因子两方面对蚁群算法进行改进,并将其应用于工程项目工期成本优化问题中。本文将改进后的蚁群算法应用于某变电站土建项目,结果表明改进后的蚁群算法其性能优于基本蚁群算法,解决了算法由于固定参数而导致的停滞问题,在工程项目工期成本优化问题的应用取得了良好的效果。

Ant colony optimization(ACO)is easy to fall in local optimum and has slow convergence rate.In order to solve the problem,this paper employs an improved ant colony optimization(IACO)algorithm which is modified in volatile factor as well as transition probability and successfully applies to time-cost optimization in specific example.Comparing with basic ant colony algorithm,this new method increases the ability of global searching and constringency,thus can settle out the stagnation of the process and find the optimum value.The results indicate that the improved ant colony algorithm is effective in time-cost optimization.