基于进度优化的项目资源集成管理研究

发布时间：2018-05-17 17:16

本文选题：项目进度问题 + 资源集成　；参考：《兰州大学》2012年硕士论文

【摘要】：在传统的资源约束项目进度问题理论中,承包商只根据他们的自有资源来安排项目进度；在该问题的派生理论——资源投资问题及资源租用问题理论中,承包商无自有资源,按照项目进度进行资源投资或租用。而在实际的商业运营中,承包商往往具有自有资源,但因资源能力有限,可能投资购买资源,或者从外部租用紧缺资源。在项目实际运作中,业主也往往对项目完成周期设置奖惩机制,允许工期提前或延迟,以鼓励承包商按期完成项目进度,节约成本。本文在原有经典理论的基础上进行拓展,打破资源与工期的严格限制,并将其统一到理论模型中,以建立一种在实际应用上更具有价值的资源集成管理模型。资源集成管理模型假定承包商拥有一定量自有资源,并允许承包商支付额外的费用从外界获取资源；业主设定项目工期及奖惩机制,承包商根据资源及工期状况安排进度,使总成本最小。本文在研究该模型结构特点的基础上改进了多模式资源约束项目进度问题对冗余模式的预处理方法,提出了适合于本问题的一种模式删除算法,经测试该模式删除算法能够显著降低问题的复杂程度。本文采用遗传算法作为主体算法,分析了按偏序结构编码及按进度结构编码两种编码方式,并设计了一种基于柔性关键链压缩的局部搜索算法嵌入遗传算法中,以提高算法的效率。最后,本文运用PROGEN生成问题库进行了数据验证,算例测试表明,采用进度结构编码的遗传算法较为有效,嵌入的柔性关键链压缩算法能够大幅度提高解的效率；解的分析表明,与经典的资源约束项目进度问题模型相比,资源集成模型能够提高项目经济效益,更具有实际意义。本文的创新点在于：将内部资源与外部资源整合集成考虑,将工期限制放开约束,与经典理论相比更加符合实际项目管理运作；提出了适合于该问题的独特的预处理方法,将冗余模式删除,大幅度降低了问题的复杂度；以往研究在解决项目进度问题的遗传算法中均采用进度编码的方式,本文尝试从偏序理论出发,按偏序结构进行编码；设计了一种柔性关键链压缩算法,加快了解的收敛速度,取得比较好的计算结果。
[Abstract]:In the traditional theory of resource constrained project schedule problem, the contractor only arranges the project schedule according to their own resources, and in the derivative theory of the problem, the resource investment problem and the resource lease theory, the contractor has no own resources. Invest or rent resources according to project schedule. In the actual commercial operation, the contractor often has its own resources, but because of the limited resource capacity, it may invest to purchase the resources, or lease the scarce resources from the outside. In the actual operation of the project, the owner often sets the reward and punishment mechanism to the completion cycle of the project, allowing the construction period to be advanced or delayed, in order to encourage the contractor to finish the project on schedule and save the cost. On the basis of the original classical theory, this paper extends the strict limitation of resources and duration, and unifies it into the theoretical model to establish a more valuable model of resource integration management in practical application. The integrated resource management model assumes that the contractor has a certain amount of its own resources and allows the contractor to pay extra costs to obtain the resources from the outside world, and the employer sets the project duration and the reward and punishment mechanism, and the contractor arranges the schedule according to the resources and the duration of the project. Minimize the total cost. In this paper, based on the study of the structural characteristics of the model, we improve the preprocessing method of the redundant pattern in the multi-mode resource-constrained project schedule problem, and propose a pattern deletion algorithm suitable for this problem. It is tested that the pattern deletion algorithm can significantly reduce the complexity of the problem. In this paper, genetic algorithm (GA) is used as the main body algorithm to analyze the coding methods of partial sequence structure coding and schedule structure coding, and a local search algorithm based on flexible key chain compression is designed to embed the genetic algorithm in the genetic algorithm. To improve the efficiency of the algorithm. Finally, this paper uses the PROGEN generating problem library to verify the data. The example test shows that the genetic algorithm based on schedule structure coding is more effective, and the embedded flexible key chain compression algorithm can greatly improve the efficiency of the solution, and the analysis of the solution shows that, Compared with the classical resource-constrained project schedule model, the resource integration model can improve the economic benefits of the project and has more practical significance. The innovation of this paper lies in the integration of internal and external resources and the release of time limit, which is more in line with the actual project management operation than the classical theory, and a unique pretreatment method suitable for this problem is proposed. The complexity of the problem is greatly reduced by deleting the redundant mode. In the past, the genetic algorithm for solving the project schedule problem adopts the way of schedule coding, this paper attempts to code according to the partial order structure from the theory of partial order. A flexible key chain compression algorithm is designed to speed up the convergence of the solution and obtain good results.
【学位授予单位】：兰州大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F062.4

【共引文献】