微粒群算法在工程项目多目标多资源均衡问题中的应用

Multi-resource Equilibrium of Multi-objective Research in Engineering Project Based on PSO Algorithm

微粒群算法(PSO)是继蚁群算法提出之后的又一种新的进化计算技术。介绍了微粒群算法的产生背景、基本算法、算法流程、算法参数,同时基于pso算法的基础上探讨在多目标下如何实现资源更有效地分配,从整体角度出发来考虑单个项目对其他正在进行的项目的影响和实施期间资源的可得性,以最合理的资源配置来满足项目中各个分目标,以达到最好的整体项目效益,为多目标下的多资源配置问题初步建立了模型。

Particle Swarm Optimization（PSO） is a new evolutionary algorithm after the ant colony algorithm.The paper introduces the background of the particle swarm algorithm,the basic algorithm,the operation process and the parameter algorithm.Based on PSO algorithm the paper has a careful study on how a single project effect other on-going projects and the availability of resources,and how to allocate resources to the best place in order to achieve the best effect of the overall project.This article also sets up a model of multi-resource equilibrium of multi-objective.