混合蛙跳算法在TCRO问题中的应用  

Application of Hybrid Frog Leaping Algorithm in TCRO Problem

作　　者：李波[1] LI Bo(Changchun Institute of Technology,Changchun 130012,China)

机构地区：[1]长春工程学院,吉林长春130012

出　　处：《现代信息科技》2020年第18期7-12,16,共7页Modern Information Technology

基　　金：长春工程学院青年基金项目(320190015)。

摘　　要：遗传算法和粒子群算法等进化算法(EAs)因其适用性被用于开发过去二十年来的多目标时间-成本资源优化(TCRO)。比较混合蛙跳算法与现有群智能算法对可分裂的TCRO问题的解决,结果表明,混合蛙跳算法比现有的群智能优化算法在寻找更好的项目进度解决方案方面具有更高的优势,其总项目成本更低,项目总项目时间更短,资源分配的总体变化或资源分配的总时间利用更少。Evolutionary algorithms(EAs),such as genetic algorithm(GA)and particle swarm optimization(PSO),have been used to develop multi-objective time-cost resource optimization(TCRO)in the past 20 years.This paper compares the hybrid frog leaping algorithm with the existing swarm intelligence algorithm in solving the divisible TCRO problem.The results show that,compared with the existing swarm intelligence optimization algorithm,the hybrid frog leaping algorithm has higher advantages in finding a better project schedule solution.The total project cost is lower,the total project time is shorter,the overall change of resource allocation or the total time utilization of resource allocation are less.

关 键 词：SFLA TCRO 群智能算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP212[自动化与计算机技术—计算机科学与技术]