多资源受限条件下工程集成管理优化问题研究

Research On Multi-Resource Constrained Project Integration Management Optimization Problem

本文建立了多资源受限条件下工程集成管理优化的模型,该模型的求解属于国际上公认的NP—hard难题之一,利用基于优先权的编码技术使得模型的求解成为可能,提出同时具有惯性权重和限定因子参数的改进版本微粒群算法,编制其matlab求解源程序,运用在以管道水平定向钻穿越工程为实例的集成管理优化模型中,微粒群算法程序在求解过程表现出了高效的搜索能力,获得了满意的优化结果。最后,着重讨论了在微粒群算法参数设计中微粒个体意识与集体意识的比较分析和微粒群种群规模与协同搜索能力的关系。

This paper set up multi--resource constrained optimization model of project integration management which belongs to international legalized NP （non- deterministic polynomial completeness）- hard problem, and by using priority--based encoding so that made solving the model possible. And then, this paper imported particle swarm optimization and advised a new version of particle swarm optimization which had both inertia weight and constriction factor parameters. The author wrote Matlab procedure and applied it in integration management optimization problem that took pipeline horizontal direction driiling project for example. Particle swarm optimization performed high efficient search capability in solving process and gained approving optimum results. In the end, this paper put stress on analyzing particle individual consciousness versus collective consciousness and the relationship between particle swarm size and ability of co --operation searching in particle swarm optimization parameter design.