【作者】 孙琦；

【导师】 钟翠萍；

【作者基本信息】 吉林大学 ， 工程项目管理， 2022， 硕士

【摘要】 随着新冠疫情在全球范围内的爆发,经济下滑趋势愈演愈烈,为了提高项目经济效益实现活下去的目标,在项目管理过程中,企业更加偏向于通过智能的调度优化方法得到最优的项目进度安排和人力资源配置计划,进而缩短项目施工周期,加快资源流转。在建筑工程项目中,由于任务数量较多,同时掌握两种及以上技能的工人数量也越来越多,这类工人可被认为是通用人力资源或者多技能工人,并且不同技能的掌握程度也存在区别。由于项目在施工过程中会遇到很多突发情况导致工期延误,项目施工将转入赶工模式,这种情况使得通过优化人力配置缩短工期的方案可行性大幅度提升。本文正是在此背景下,主要研究了工程项目中的通用人力资源配置优化问题,并且对其进行拓展,扩充现有的研究领域。首先,本文定义了何为多模式下不同熟练度的通用人力资源配置问题,进行详细的问题描述,介绍了问题的约束条件和优化目标,建立了混合整数规划模型,并利用CPLEX软件对一组具有代表性的仿真数据进行验证,证明数学模型的可行性。其次,由于CPLEX软件仅适用于小规模数据的求解,因此本文采用一种人工免疫系统算法,从算法基本原理、工作机制和特殊性等出发,根据建立的数学模型提出改进的编码解码方案以及相应的算法流程,对多模式下不同熟练度的通用人力资源配置问题求解。最后,为了验证算法的有效性,本文采用已有研究的三种具有代表性的算法作为对比对象,利用调研所得到的一组实验数据通过MATLAB软件进行编码验证。并在此基础上扩大任务、工人及同时拥有的技能数量,采用随机生成技能组合和熟练度组合的方法进行大规模算例验证,通过比较每种算法得到的工期偏差百分比的平均值验证算法的通用性。结果表明,同另外三种算法相比,本文所提出的算法显著性的缩短了项目工期,可在实际生产工作中应用推广。更多还原

【Abstract】 With the outbreak of COVID-19 in the world,the economic downturn is becoming more and more intense.In order to achieve the goal of survival and improve the economic benefits of the project,in the process of project management,enterprises are more inclined to get the best project scheduling and human resource allocation plan through intelligent scheduling optimization method,thereby shortening the construction cycle and speeding up the circulation of resources.In construction projects,due to the large number of tasks,more and more workers master two or more skills at the same time,and there are differences in the degree of mastery of different skills.At the same time,due to the delay of construction period caused by many emergencies in the construction process,the project construction will turn to the rush mode,This situation greatly improves the feasibility of using manpower allocation optimization to shorten the construction period.Under this background,this paper mainly studies the optimization of general human resources allocation in engineering projects,expands it and expands the existing research fields.Firstly,this paper defines what is a multi-mode multi-skilled human resource scheduling problem with different proficiency,describes the problem in detail,introduces the constraints and optimization objectives of the problem,establishes a mixed integer linear programming model,and uses CPLEX software to verify a group of representative simulation data to prove the feasibility of the mathematical model.Secondly,since CPLEX software is only suitable for small-scale data,this paper proposes to adopt an improved artificial immune system algorithm(NAIS),considering the role of T cells in the immune system from the basic principle,working mechanism and particularity of the algorithm,and formulate a suitable coding and decoding scheme and corresponding algorithm flow according to the established mathematical model,Solve the heterogeneous multi-skill scheduling problem under multi-mode.Finally,in order to verify the effectiveness of the algorithm,this paper uses three representative algorithms as the comparison object,obtains a set of experimental data by investigation,encodes it by MATLAB software,and verifies the effectiveness of the algorithm by comparing the optimization scheme and fitness function curve obtained by each algorithm.The results show that compared with the other three algorithms,the algorithm proposed in this paper significantly shortens the project duration,and the convergence degree is stronger than other algorithms,which can be applied and popularized in practical production.更多还原