【作者】 李晨；

【导师】 侍洪波； 单伟；

【作者基本信息】 华东理工大学 ， 控制工程， 2011， 硕士

【摘要】 蚁群算法,是一种新型的智能进化计算方法,蚂蚁在觅食过程中能够在所经过的路径上留下一种称之为信息素的物质,而且蚂蚁在寻找食物的过程中能够感知这种物质的存在及其强度,而且以此指导自己的运动方向,他们倾向于朝着强度高的方向移动。因此,由大量蚂蚁组成的集体觅食行为就表现出一种信息正反馈现象：某一路径越短,该路径上走过的蚂蚁就越多,所留下的信息素强度也就越大,后来者选择该路径的概率因此就越大；蚂蚁个体之间通过这种信息交流来选择最短路径并达到搜索食物的目的,蚁群优化算法就是模拟蚁群这一觅食行为的优化算法。对于蚁群算法仍然有其局限性,而这些局限性可以通过适应机制的提出而得到相应的解决。工程项目管理是一个工程项目建设的重要环节,物料的准确到达,并能够按要求安装,对于工程本身起到了决定性的作用。本文所涉及的自适应蚁群优化算法与工程项目管理有机的结合,以及有效地解决整个工程供应链管理的优化问题,从而优化了工程项目管理的路径选择,达到了优化的目的。我们可以将物料看成是蚁群算法中的蚂蚁,在整个工程供应链的过程中怎样让这些“蚂蚁”在每一个流程中调度或是走出的路径得到最大程度的优化,从而使整个工程项目达到一种进度以及成本的相对优化,这也是文章的研究重点。更多还原

【Abstract】 Any Colony Algorithm, is one advanced calculation algorithm currently. During searching food, ants normally leaves one kind of information pheromone on the ways they walked. Meanwhile, ants all can judge the pheromone if it is weak or strong. Usually, ants follow stronger pheromone to trace the food. Therefore, we can regard this behavior as one kind of positive reaction:The shorter route has, the more ants will pass and the stronger pheromone left on the route, more change to next ant will be this route. Through this way, ants communicate among themselves and trace the food accordingly. Any Colony Algorithm is a kind of simulation of the ant behavior. Of course, Any Colony Algorithm itself still has limitation for practice so far, but Adaptive Any Colony Algorithm can be used in some areas.Project Supply Chain is the most important part of entire project. The deliverable materials is the necessary factor to lead one successful project. The Adaptive Any Colony Algorithm can give one optimization solution to the project supply chain; it can improve the efficiency of practical execution. During entire project, we can regards the ant as the material, we can arrange every ant to go one optimized route, this is similar with the material going one best way to final installation. So that the project will reach one optimized result. This is core of this paper.更多还原