层次分析法优秀论文3
层次分析法论文

本科生毕业论文
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每年一度的奖励时,绩效考核结果是重要的依据。 4)人事调整:人事调整必须严格与人事考核的结果结合起来,各类企 业根据自身情况,制定相应的升迁基准和等级。 5)薪资调整:根据绩效考核的结果对薪资做适当的调整,以调动员工 的积极性。 6)横向比较:将工作成果与目标比较,考察员工工作绩效如何。 7)纵向比较:员工之间的绩效比较,找出不足之处。 (2)对主管来说 1)帮助下属建立职业工作关系。 2)借以阐述主管对下属的期望。 3)了解下属对其职责与目标任务的看法。 4)取得下属对主管、公司的看法和建议。 5)提供主管向下属解释薪资处理等人事决策的机会。 6)共同探讨员工的培训和开发的需求及行动计划。 (3)对员工来说 1)加深了解自己的职责和目标。 2)成就和能力获得上司的赏识。 3)获得说明困难和解释误会的机会。 4)了解与自己有关的各项政策的推行情况。 5)了解自己在公司的发展前程。 6)在对自己有影响的工作评估过程中获得参与感。 现归结如图 2-1。
组织共同目标组织绩效的衡量标准
部门特定目标部门绩效的衡量标准
上司为下属列示 目标和衡量标准
员工为自己计划 目标和衡量标准
与员工达成共同的目标与衡量标准 回顾组织的 绩效状况 中期考核提供有关已建立目 标完成程度的反馈信息
不适部分调整 新增部分加入
按照已建立或修正的目 标对员工进行绩效评估 图 2-2 目标管理法程序[5]
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本科生毕业论文
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2 绩效考核理论概述
2.1 绩效考核的概念
2.1.1 绩效考核的定义 绩效考核[1]是一种正式的员工评估制度,它是通过系统的方法、原理来 评定和测量员工在职务上的工作行为和工作效果。员工绩效考核是“按照一 定的标准,采用科学的方法,检查和评定企业员工对职务所规定的职责的履 行程度,以确定其工作业绩的一种有效的管理办法”。 就像 Bates 和 Holton(1995)提出的那样,“绩效是一个多维建构[2], 观察和测量的角度不同,其结果也不同”。我们从不同的科学领域出发来认 识绩效,所得到的结果也有所差异。 从管理学的角度看,绩效是组织期望的结果,是组织为实现其目标而展 现在不同层面上的有效输出,它包括个人绩效和组织绩效两个方面。组织绩 效是建立在个人绩效实现的基础上,但是个人绩效的实现并不一定保证组织 是有绩效的。 从经济学的角度看,绩效与薪酬是员工与组织之间的对等承诺关系,绩 效是员工对组织的承诺, 而薪酬是组织对员工做出的承诺。 一个人进入组织, 对组织要求的绩效做出承诺,是进入组织的前提条件。当员工实现了他对组 织的承诺,组织就实现其对员工的承诺。这种关系体现了等价交换的原则, 而这一原则正是市场经济运行的基本规则。 从社会学的角度上看,绩效以每个社会成员按照社会上所确定的角色承 担他的那一份职责。他的生存权利是由其他人的绩效保证的,而他的绩效又 保证其他人的生存权利。因此,出色的完成他的绩效是他作为社会成员的义 务,他受惠于社会就必须回馈社会。 2.1.2 绩效考核的作用 (1)对公司来说[3] 1)员工培训:管理者以及培训工作负责人,在进行培训需求分析时, 应把人事考核的结果作为员工是否需要培训,对员工实行 有针对性的指导,改善和提高员工的工作绩效。 3)适时激励:对考核结果优异者或突出者,给予一定的奖励。在决定
层次分析法 论文

欧洲五大足球俱乐部的数学建模分析论文统计学杨子清 101201010117前言:纵观当今欧洲足坛,风起云涌,豪强并起。
巴萨皇马,称雄西甲;德甲拜仁,一枝独秀;蓝黑军团国际米兰,逐鹿意甲之天下;英超一霸切尔西,竟然也能在高手如林的欧冠赛场捧杯。
欧洲的足球水平为何如此之高?五大豪强的经验又带给了我们什么样的启示呢?这便是本文要探讨的问题。
本文引用了数学建模的思想,采用了层次分析法对欧洲五大足球俱乐部的综合实力进行理性而深入的分析。
所谓数学建模,就是对现实世界中的某一特定现象,为了某一特定的目的,做的简化假设,运用数学工具,得到一个数学结构。
而层次分析法,是建模中常用的方法之一。
通过层与层之间的对比分析,得出实际问题中的某些结论。
本文所研究的问题是关于五大足球俱乐部的综合实力排名情况。
现实的足球世界中,影响一支球队的综合能力有许多。
例如进攻能力、防守能力、球员能力、教练的执教能力、裁判的执法能力等。
这些因素都是对于一支的球队综合实力有着或多或少的影响。
但他们各自的权重并不一样,所以,如何筛选这些因素是本文分析的关键所在。
众所周知,当数学模型建立之后,还不能马上用于实际分析,必须对模型做进一步的检验。
由于本文数据分析过程较为繁琐,所以检验部分并非人工完成,而是运用电脑软件R来完成的。
采用了Satty的检验方法对模型进行分析,使模型分析的可信度大大提高。
关键词:数学模型、层次分析法、欧洲足球一、数学建模的基本过程:如下图所示图1:数学建模基本流程图层次分析法把人的思维层次化、数量化, 并用数学为分析、决策、预报或控制提供定量的依据。
这一方法的特点是在对复杂决策问题的本质、影响因素以及内在关系等进行深入分析之后, 构建一个层次结构模型, 然后利用较少的定量信息, 把决策的思维过程数学化, 从而为求解多目标、多准则或无结构特性的复杂决策问题提供一种简便的决策方法 , 尤其适合于人的定性判断起重要作用的、对决策结果难于直接准确计量的场合。
层次分析法经典案例

层次分析法经典案例篇一:层次分析法步骤层次分析法实例与步骤结合一个具体例子,说明层次分析法的基本步骤和要点。
【案例分析】市政工程项目建设决策:层次分析法问题提出市政部门管理人员需要对修建一项市政工程项目进行决策,可选择的方案是修建通往旅游区的高速路(简称建高速路)或修建城区地铁(简称建地铁)。
除了考虑经济效益外,还要考虑社会效益、环境效益等因素,即是多准则决策问题,考虑运用层次分析法解决。
1.建立递阶层次结构应用AHP解决实际问题,首先明确要分析决策的问题,并把它条理化、层次化,理出递阶层次结构。
AHP要求的递阶层次结构一般由以下三个层次组成:? 目标层(最高层):指问题的预定目标;? 准则层(中间层):指影响目标实现的准则;? 措施层(最低层):指促使目标实现的措施;通过对复杂问题的分析,首先明确决策的目标,将该目标作为目标层(最高层)的元素,这个目标要求是唯一的,即目标层只有一个元素。
然后找出影响目标实现的准则,作为目标层下的准则层因素,在复杂问题中,影响目标实现的准则可能有很多,这时要详细分析各准则因素间的相互关系,即有些是主要的准则,有些是隶属于主要准则的次准则,然后根据这些关系将准则元素分成不同的层次和组,不同层次元素间一般存在隶属关系,即上一层元素由下一层元素构成并对下一层元素起支配作用,同一层元素形成若干组,同组元素性质相近,一般隶属于同一个上一层元素(受上一层元素支配),不同组元素性质不同,一般隶属于不同的上一层元素。
在关系复杂的递阶层次结构中,有时组的关系不明显,即上一层的若干元素同时对下一层的若干元素起支配作用,形成相互交叉的层次关系,但无论怎样,上下层的隶属关系应该是明显的。
最后分析为了解决决策问题(实现决策目标)、在上述准则下,有哪些最终解决方案(措施),并将它们作为措施层因素,放在递page1阶层次结构的最下面(最低层)。
明确各个层次的因素及其位置,并将它们之间的关系用连线连接起来,就构成了递阶层次结构。
层次分析方法范文

层次分析方法范文案例背景:小明是一名大学生,想要购买一辆新车。
他希望车辆的品牌知名度高、车辆性能好、价格合理等因素都可以考虑到,从而做出最佳决策。
步骤一:建立层次结构在层次分析方法中,首先需要建立一个层次结构,包含了问题的各个方面,以及它们之间的关系。
对于小明的问题,他可以将层次结构分为三个层次:品牌知名度、车辆性能和价格。
步骤二:构建判断矩阵判断矩阵是层次分析方法的核心,用于比较不同因素之间的重要程度。
小明需要根据他对每个因素的主观判断来构建判断矩阵。
例如,他认为品牌知名度比车辆性能重要,可以给予品牌知名度一个更高的权重。
在这个过程中,小明需要和他对车辆品牌的了解程度进行比较,以及和他对车辆性能的需求进行比较。
步骤三:计算权重向量通过对判断矩阵进行计算,可以得到每个因素的权重向量。
小明可以使用软件或者Excel等工具来进行计算。
权重向量表明了不同因素对最终决策的影响程度。
例如,如果品牌知名度的权重向量为0.6,车辆性能的权重向量为0.3,价格的权重向量为0.1,则表明品牌知名度对最终决策的影响最大。
步骤四:一致性检验在确定权重向量之后,需要进行一致性检验来验证判断矩阵的合理性。
一致性检验可以使用一致性指标CI和一致性比例CR来进行评估。
如果CR值小于0.1,则说明判断矩阵是一致的。
如果CR值大于0.1,则需要重新调整判断矩阵,直到CR值小于0.1为止。
步骤五:综合评估与决策通过计算得到的权重向量,可以对各方案进行综合评估,从而做出最佳决策。
小明可以将不同品牌的车辆在品牌知名度、车辆性能和价格等方面进行评估,然后乘以对应的权重向量,得到综合评估分数。
最终,小明可以选择综合评估分数最高的车辆作为他的购买决策。
层次分析方法是一种科学而系统的决策方法,可以帮助我们在面对复杂问题时做出更加准确的决策。
通过对层次结构的建立,判断矩阵的构建,权重向量的计算以及一致性检验的评估,可以得出最佳决策方案。
同时,在进行层次分析方法时,我们还应该注意对各个因素进行实际情况的分析和评估,以保证最终的决策是科学和合理的。
国赛层次分析法论文

国赛层次分析法论文摘要:本文针对消费者购房这一具体问题,基于高等代数矩阵内容,立足于数学建模,通过具体实例的分析详细描述了采用层次分析法解决多目标决策问题的方法和步骤,为消费者的购房决策提供科学合理的办法。
关键词:成对比较矩阵;特征根;特征向量;层次分析法随着经济的发展,收入水平的增加,消费者对商品房的要求也在增加。
目前多数消费者购房有的因为工作,有的是为了改善居住环境,还有的是为了投资。
不管是什么原因,由于涉及金额巨大,购房需慎之又慎,以免花钱买后悔。
针对消费者的需求,房地产开发商也在不断地推出新的楼盘。
这些楼盘往往各有各的特点,这使得消费者经常因选房而筋疲力尽,生怕捡了芝麻丢了西瓜。
究其原因,主要是考虑的因素太多,价格、交通、环境等等。
如就价格而言,甲比乙便宜;而就交通而言,乙又不如甲,这就使得购房者难以做出孰优孰劣的判断。
但是,所有的购房者都想买到物美价廉的房子,这是总目标,如果我们能够对备选房源“物美价廉”的程度进行量化,就能通过简单的数值比较做出决策。
运用统计学中的层次分析法就能轻松解决这一决策难题。
一、层次分析法概述1简介层次分析法是美国运筹学家萨蒂在20世纪70年代提出的一种实用的定性和定量相结合的多准则决策方法。
它是把复杂的决策按照目标层、准则层、子准则层、方案层的顺序表示为一个有序的递阶层次结构,通过人们的比较判断,计算各种决策方案在不同准则及总目标之下的相对重要性权重,从而把难以量化的各种方案定量化,以得到各种方案的相对优劣的排序值,并据此做出最后的决策。
2层次分析法的基本步骤第一步:根据问题的性质和要求,提出一个总目标。
将目标逐层分解为几个层次,建立层次结构模型。
第二步:对同一层次的各元素关于上一层次某一准则的重要性进行两两比较并赋权值,构造成对比较矩阵。
基于层次分析法的模糊综合评价研究和应用共3篇

基于层次分析法的模糊综合评价研究和应用共3篇基于层次分析法的模糊综合评价研究和应用1基于层次分析法的模糊综合评价研究和应用层次分析法(Analytic Hierarchy Process,简称AHP)是一种重要的多指标决策方法,其独特的定量分析模式使其被广泛应用于各种决策场景中。
然而,在实际应用过程中,AHP所依赖的判断矩阵等参数很难满足严格的一致性要求,这就使得AHP方法的有效性存在一定的争议。
针对这一问题,模糊综合评价方法应运而生,它将AHP和模糊理论相结合,充分考虑了决策者的不确定性和模糊性,从而提高了决策效果。
本文将通过研究和应用实例,探究基于层次分析法的模糊综合评价方法的优点和不足,以及如何选取决策指标和构建评价体系。
1. 模糊综合评价方法概述模糊综合评价方法是一种基于模糊数学的决策方法,可以较好地处理决策过程中存在的不确定性和模糊性。
它的基本思想是,将决策问题转化为一个多层次、多指标的评价体系,在每个层次上进行相对重要性的判断和权重赋值,最终得出总体评价结果。
模糊综合评价方法中的模糊数常常用梯形和三角形模糊数表示,如图1所示。
图1 模糊数表示法其中,如(a)所示的梯形模糊数由四个参数a、b、c、d唯一确定,表示变量值在[a,b]和[c,d]之间的可能性;如(b)所示的三角形模糊数由三个参数a、b、c唯一确定,表示变量值在[a,c]之间的可能性。
2. 决策指标的选取和构建评价体系在使用模糊综合评价方法进行决策时,决策指标的选取和评价体系的构建是很关键的。
具体来说,决策指标应具备以下特点:(1) 目标明确:决策指标应当明确对应的决策目标,且目标应该是具有明确定义的。
(2) 可度量性强:决策指标应当具有可度量性和数量化的特点,以便进行量化分析。
(3) 影响因素少:决策指标应当尽量减少具有交叉影响的因素,以避免多重计数和重复计算。
(4) 数据可获取性高:决策指标的数据应当便于获取,能够反映决策现实,以便进行实际应用。
层次分析法 (3)

层次分析法1. 介绍层次分析法(Analytic Hierarchy Process,AHP)是一种用于多准则决策分析的方法。
该方法由美国运筹学家托马斯·L·塞蒂在1970年代初开发并广泛应用于各个领域。
层次分析法通过将复杂的决策问题分解成多个层次,并对不同层次的准则进行比较和评价,帮助决策者做出科学、合理的决策。
2. 基本原理层次分析法的基本原理是将一个复杂的决策问题层层分解为若干个层次。
这些层次由目标层、准则层、方案层等组成,形成一个层次结构。
在每个层次上,决策者需要对不同的元素进行比较和评价,以确定它们之间的重要性和优先级。
层次分析法的核心是通过建立成对比较矩阵,从而将主客观因素相结合,实现准则之间的比较和权重的确定。
在层次分析法中,决策者需要对每个准则对两两进行比较,根据重要性进行两两判断。
这些判断形成了一个判断矩阵。
然后,通过特征向量法计算各个准则的权重。
最后,将这些权重进行归一化处理,得到每个准则的相对重要性。
3. 应用步骤层次分析法的应用可以按照以下步骤进行:3.1 确定决策目标首先,需要明确决策的目标是什么。
目标是整个决策过程的核心,决策者需要明确目标才能有针对性地进行后续的决策分析。
3.2 构建层次结构根据决策问题的特点和要求,构建一个包含目标层、准则层和方案层的层次结构。
目标层表示决策的最终目标,准则层表示影响目标实现的各种准则,方案层表示可供选择的各种方案。
3.3 构建比较矩阵对于每个层次的准则,决策者需要对其进行两两比较,并判断各个准则之间的重要性。
通过构建比较矩阵,可以很直观地展示各个准则之间的相对重要性。
3.4 计算权重通过特征向量法,根据比较矩阵计算各个准则的权重。
特征向量法是一种数学方法,可以根据比较矩阵的特征向量,得到每个准则的权重。
3.5 归一化处理将准则的权重进行归一化处理,得到每个准则的相对重要性。
归一化处理可以使不同准则的权重在同一尺度上进行比较,更加公平合理。
层次分析法论文(20210228083738)

多目标规划结课论文论文题目:层次分析法在人才招聘中的应用研究如何从众多的应聘者中甄选出适合于本企业的人才是人力资源管理所面临的重要课题之一。
目前用人单位在招聘员工时,通常只是对众多的应聘人员进行简单的考察。
因受各种主客观因素的影响,对应聘人员的评价难免有失公正。
文章以某大型企业高层次人才的胜任力模型为例,设计了在招聘过程中甄选应聘者的指标体系,在评估方法上,采取定性与定量相结合的方法,运用层次分析法(AHP)确定了指标权重系数,针对甄选指标的模糊性,建立了评估的模糊综合评价模型,并进行了应用实例评估,结果表明,所建立的应聘者甄选评估体系是实际可操作的。
关键词:胜任力模型;层次分析法;模糊评价随着我国经济的飞速发展,人才已成为各企业竞争的核心要素。
这当中,人才招聘是企业实施人才战略,合理配置人才梯队最为基础性的工作,同时对于企业提升人才队伍整体水平有着至关重要的意义。
从企业人力资源规划角度出发,员工招聘规划是企业人力资源规划最为基础性、决定性的工作,员工招聘规划的合理性直接对企业人力资源规划中后续工作产生重要的影响。
图1揭示了员工招聘规划在企业人力资源规划中扮演的重要角色,充分体现了人才招聘在企业战略发展中的重要意义。
在人才招聘的工作中,常常会遇到许多模糊的概念,例如,人才业务能力的大小、思想水平高低、身体状况等。
传统的人才招聘工作中,多采用团队针对应聘者多方面表现,综合评价进行人才甄选,该方法虽然采用团队综合评价,但由于团队中领导者的导向作用会对团队成员对应聘者评价有不同程度的影响,而且团队成员做出的评价本身都具有主观性,导致最终的结果客观性不强,且针对不同应聘者的可比性不够。
模糊优选的基本理念是将模糊的问题通过合理的评定、比较实现量化,将模糊优选模型应用于人才招聘问题中,可实现将模糊问题清晰化,同时在此基础上引入层次分析法,对人才模糊优选中的各影响因素赋予合理权重,最终实现人才招聘的规范化、客观化。
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For office use onlyT1________________ T2________________ T3________________ T4________________Team Control Number55069Problem ChosenAFor office use onlyF1________________F2________________F3________________F4________________ 2017 MCM/ICM Summary SheetThe Rehabilitation of the Kariba Dam Recently, the Institute of Risk Management of South Africa has just warned that the Kariba dam is in desperate need of rehabilitation, otherwise the whole dam would collapse, putting 3.5 million people at risk. Aimed to look for the best strategy with the three options listed to maintain the dam, we employ AHP model to filter factors and determine two most influential criteria, including potential costs and benefits. With the weight of each criterion worked out, our model demonstrates that option 3is the optimal choice.According to our choice, we are required to offer the recommendation as to the number and placement of the new dams. Regarding it as a set covering problem, we develop a multi-objective optimization model to minimize the number of smaller dams while improving the water resources management capacity. Applying TOPSIS evaluation method to get the demand of the electricity and water, we solve this problem with genetic algorithm and get an approximate optimal solution with 12 smaller dams and determine the location of them.Taking the strategy for modulating the water flow into account, we construct a joint operation of dam system to simulate the relationship among the smaller dams with genetic algorithm approach. We define four kinds of year based on the Kariba’s climate data of climate, namely, normal flow year, low flow year, high flow year and differential year. Finally, these statistics could help us simulate the water flow of each month in one year, then we obtain the water resources planning and modulating strategy.The sensitivity analysis of our model has pointed out that small alteration in our constraints (including removing an important city of the countries and changing the measurement of the economic development index etc.) affects the location of some of our dams slightly while the number of dams remains the same. Also we find that the output coefficient is not an important factor for joint operation of the dam system, for the reason that the discharge index and the capacity index would not change a lot with the output coefficient changing.Contents1Overview (1)1.1Background (1)1.2 Restatement of the Problem (1)1.3 Literature Review (2)2Assumptions and Justifications (2)3Notation (3)4Model Overview (4)5Model Theory (5)5.1Determination of the Number and Location of the Dams (5)5.2 Joint operation of dam system model (9)6Model Implementation and Results (11)6.1The Number and Location (11)6.2The Strategy of Modulating Water Flow (14)7 Sensitivity Analysis (15)7.1 The Model of Determination of the Number and Location (15)7.2 The Model of Modulating Water Flow (17)8 Further discussion (17)9 Strengths and Weaknesses (18)9.1 Strengths (18)9.2 Weaknesses (19)10 Conclusion (19)11 The Evaluation of Three Options (20)11.1 Establish a Hierarchical Model (20)11.2 Analysis and Results (21)1 Overview1.1 BackgroundA Zambezi River Authority conference was held in March 2014, engineers warned that the foundations of the dam had weakened and there was a possibility of dam failure unless repairs were made.On 3 October 2014 the BBC reported t hat “The Kariba Dam is in a dangerous state. Opened in 1959, it was built on a seemingly solid bed of basalt. However, in the past 50 years, the torrents from the spillway have eroded that bedrock, carving a vast crater that has undercut the dam’s foundations, engineers are now warning that without urgent repairs, the whole dam will collapse. If that happened, a tsunami-like wall of water would rip through the Zambezi valley, reaching the Mozambique border within eight hours. The torrent would overwhelm Moz ambique’s Cahora Bassa Dam and knock out 40% of southern Africa’s hydroelectric capacity. Along with the devastation of wildlife in the valley, the Zambezi River Authority estimates that the live of 3.5 million people are at risk.”On February 2015, Engineers have started on a R3.3bn rescue marathon to prevent the “catastrophic failure” of the Kariba Dam. According to a World Bank special repor t on the beleaguered structure-one of the biggest man-made dams in the world-a potential wall collapse threatens the lives of about 3-million people living on the Zambezi River floodplain between the hydro scheme on the Zambia-Zimbabwe border and the Mozambique coast. [1]1.2 Restatement of the ProblemWe are required to provide an overview of potential costs and benefits with the three options already listed. Then we need to establish a model to determine the number and placement of the new dams when removing the Kariba dam along the Zambezi River. The same overall water management capabilities are also needed. In addition, we should consider emergency water flow situations and restrictions regarding the locations and time, so that we could give out the strategy for modulating the water flow through our new multiple dam system.In order to solve those problems, we will proceed as follows:●Build a model to determine the number and location of the multiple dams.●Give the corresponding strategy of modulating water flow in different conditions.In our model, we first establish a multi-objective model and use genetic algorithm determine the number and location of the multiple dams. There are two goals improving the water resources management capacity and reducing the cost. Besides, we add some constraints such as water balance, water level, safety and water protection. We choose twenty suitable dam sites and employ the genetic algorithm to solve the optimal problem to determine the number and the location.After determining the number and location of the dams, we construct our joint operation of damsystem model and employ the genetic algorithm to solve the problem based on the thought of dynamic programming. According to the Kariba’s climate data for about 30 years, we abstract normal flow year, low flow year, high flow year and differential year. We use them to work out the water resources planning and scheduling strategy. The construction of the discharge index and the capacity index benefits an analysis and evaluation for joint operation of the dam system’s performance in different month and year.1.3 Literature ReviewDating back to 2004, the United States removed 72 dams in total, which created a historical record. Therefore, it is high time for us to focus on the construction of dams concerning their number and placement. Plenty of researchers have already made a number of notable papers to address these problemsAlfer Weber (1909) first proposed a framework for location problem, which is an allocation question with respect to space resource. Among the three classical location model, set covering problem is a significant branch of siting issues. They explored a multi-objective location model to tackle problems with siting optimal points. In their model, maximizing coverage rate in order to satis fy every place’s need is the target function, the concentric point and the capacity restrictions are constraint conditions. Thus, they could convert the optimization problem to the mixed integer linear programming question.After the set covering model was established, we can optimize our choice of siting the dams. Then several scientists were devoted to building an optimal operation model to provide a reasonable balance between safety and balance. They begin to figure out how the multiple dam system would benefit or affect each other within its system. Masse(1940) first illustrated the concept of it; their main computing method was to optimize water modulating strategy during dispatching period.Further studies are carried out about different methods to investigate the optimal operation model, including dynamic programming algorithm and neural network algorithm based on improved computer technique. Also, there is much theoretical analysis about location problem since 1990. John Current and Morton O'Kelly(1992) suggested using a modified version of the set covering location model, which still didn’t take the reality into account.2 Assumptions and JustificationsTo simplify our problems, we make the following basic assumptions, each of which is properly justified.●The dam system is built downstream in the valley of the Kariba Dam. Because it’smore convenient to build and also with less cost, which can be easily implemented.●The cost of the dam is mostly the same. Owing to the fact that the length of the canyonis not large(24km),geological conditions and climate conditions are mostly the same.● Each dam’s water supply is mostly the same. Taking into account of safe operation ofthe entire multi-dam system, we should make the burden of each dam to be the same as much as possible.● The water quality of the dam system is the average of the water quality between thetwo reservoirs. The river is flowing, so the water quality is mostly similar.● Water of the dams downstream only comes from dams upstream and naturalprecipitation. According to Google Maps, there are no tributaries near the canyon. Also with the principle of conservation of water, the formula should be maintained.3 NotationAbbreviation Description{}12,,m Y y y y = The set of cities{}12=,,n X x x x The set of dams(,)i n d y X The distance from the th i city to the nearest smaller dami Ele The electricity demand of th i cityi Wat The water demand of th i city(,)W t i The discharge amount of the th i dam at the end of period t,(,)Z t i The total amount of water released during period t(,)T t i The amount of natural water in period tij V The volume in the th j period of the th i damij Q The inflow in the th j period of the th i damij q The discharge volume in the th j period of the th i damij QJ The runoff volume between the th i dam and the (1)th i -damij S The actual water supply th i dam in the th j periodij D The planned water supply of the th i dam in the th j periodij H The hydraulic head of th i dam in the th j periodi K The fore-voltage factor of the th i damt λ The discharge flow indicators in the th t periodt μ The storage capacity indicators in the th t period4 Model OverviewTo provide a detailed analysis of the option (3)-removing the Kariba dam and newly building ten to twenty smaller dams. We need to determine the number and location of the multiple dams first. And on that basis we must establish a model to modulate the water flow through the multiple dam system to adapt to different situations. A reasonable balance between safety and cost of our strategy is also needed.Our first model allows us to determine the number and the location of the multiple dams. We regard the optimal problem as a set covering problem and establish a multi-objective model to solve the problem. There are two goals, namely improving water resources management capacity and reducing the cost. And there are also some constraints including water balance, water level, safety, water resources protection and number constraints. On the account that the optimal problem is difficult to solve in polynomial time, so we use genetic algorithm to get the solution.After determining the numbers and the location, we establish a joint operation of dam system model to gain a strategy about modulating water flow in different condition. Though it’s also a multi-objective problem, it is different from the previous model. We use the maximization of economic and social benefits as the objective and set some constraints, such as water balance, reservoir capacity and discharge flow constraints. We use genetic algorithm to get themodulating strategy in different conditions.In conclusion, we use programming and heuristic algorithm to solve the problem of building dams and the modulating strategy. It’s relatively easy to achieve and it has a significant guidance for the reality.5 Model Theory5.1 Determination of the Number and Location of the Dams5.1.1 Establishment of the modelThe construction of dams needs to consider many aspects, while at the same time it is subject to economic, social, environmental constraints and other factors. In order to obtain the proper number of dams and their location, we establish a multi-objective model.The Objective● Improve Water Resources Management CapacityThe purpose of building smaller dams instead of larger dams is to manage water resources better, mainly to satisfy dweller’s demand for the electricity consumption and water consumption (Including agricultural, industrial and domestic water) of the neighboring cities. Demand may vary between cities, but it is clear that for cities with greater demand, the dam should be built closer to them. so we get that1min (,)mi i n i Ele d y X =∑1min (,)mi i n i Wat d y X =∑● Reduce the CostOn the basis of ensuring the water supply and power supply, we should minimize the cost of our plan. The whole cost consists of the removal of the Kariba dam and building new smaller dams. Since the cost of removal is fixed, so we only consider the variable cost(building cost), which is only related to the number of dams. So we should minimize the quantity of the smaller dams.min nThe Constraints● Water Balance()(,)(1,)(,)(,)k i W t i W t i Z t k T t i π∈=-++∑(,)W t i ,(,)Z t i and (,)T t i represent the discharge amount of the th i dam at the end of periodt, the total amount of water released during period t and the amount of natural water in period t respectively.()i π denotes the set of all higher dams of th i dam. If ()i π is empty, the corresponding summation is zero.[2]● Water LevelThe water level in the dam area should be kept between the dead water level and the limited water level in the flood season. Dead Water Level, namely the lowest water level that allows a reservoir to fall off under normal operating conditions. Flood limited water level is the requirements of control over flood to limit reservoirs’ water storage.DWL WL FWL ≤≤● SafetyThe construction of multiple smaller dams is at least as safe as the original larger dams. The safety considerations for dam construction mainly include reducing the probability of dam failure, thereby reducing damage to dams downstream and enhancing resistance ability to extreme weather.sd Bd Safety Safety ≥sd Safety represents the safety of multiple dams system, while Bd Safety denotes the safety ofthe existing Kariba dam.● Water Resources ProtectionThe construction of smaller dams should require a higher degree of protection for the water resources as the replacement of the existing dam.sd Bd WRP WRP ≥sd WRP represents the environment protection of the multiple dams system, while Bd WRP denotes the environment protection of the existing Kariba dam.● NumberThe number of small dams should be greater than ten and less than twenty. Option 3 is replacing the Kariba dam with a series of ten to twenty smaller dams.To ensure the continuity of the model establishment, the parameters of the constraints will be described in the next part. And in the sixth section, we will clarify how to calculate the demand of electricity(i Ele ),the demand of the water(i Wat ),the safety of different dams and theenvironment protection of different dams.To sum up, we model the problem about smaller dams’ number and location decision with multi-objective optimization. The formulas of this model is1min (,)mi i n i Ele d y X =∑1min (,)m i i n i Wat d y X =∑min n..S t ()(,)(1,)(,)(,)k i W t i W t i Z t k T t i π∈=-++∑ DWL WL FWL ≤≤sd Bd Safety Safety ≥sd Bd WRP WRP ≥1020n ≤≤(n=10, 11, 12…..20)5.1.2 The Parameter of the Constraints● The Demand of ElectricityThe power demand of a city is mainly related to its economic and demographic factors. Our paper uses the city's latest available GDP data as the representative of its economic factors, and the total urban population as the representative of its demographic factor.The GDP of the th i city is i GDP .The population of the th i city is i pop .● The Demand of WaterThe water consumption of residents is mainly affected by residents' income, water price and other factors. Since within a country, the price difference is relatively small, so here we ignore the price difference.. Therefore, the water consumption of urban residents is mainly affected by the income of residents, We use the city's GNI to represent its urban residents. The GNI of the th i city is i GNI .● The Safety of Dams and the Kariba Dam [3]For the safety of dam construction, our paper mainly consider the index of risk loss as the agent of its safety indicators.For a single Big dam, its Risk Loss Index(RLI) Bd R equals to P multiply N . P is the failure probability of the dam beyond the current code standard. For example, the current code specifies that if a dam's seismic safety standard is 50 years beyond 10%, the probability offailure exceeding the current code specification is 0.1 / 50 = 0.002.N is the life loss of dam failure (we can convert economic loss into life loss in a certain percentage). We use the Dekay & McClelland method to calculate the loss. Thus, the RLI of the Kariba dam is()()Bd R P K N K =⋅.For multiple dam system, the RLI of the th j dam is1()()(|)()()nj l j R P j N j P l j P j N l =+=⋅+⋅⋅∑and the RLI of the multiple dam system is 1nsdsdj j R R ==∑ The safety of the multiple dam system should be greater than or at least equal to the safety of the existing Kariba dam. So we get that sd BdR R ≤, that is to say 1()()nsd i i R P K N K =≤⋅∑.And n is an integer greater than ten and less than twenty● The water resources protection of damsAccording to the International Commission On Large Dams(ICOLD), there are three goals of water resources management [4]✓ Improved management of the water supply✓ Improved water quality in our rivers✓ Improved environmental conditions in the watershedSince there are few branches in the Kariba Gorge, we mainly consider the management of the water supply and the water quality.According to the constraints, the water supply of the multiple-dam system should be greater than the big dam. That is to saysd Bd WS WS ≥sd WS equals to the number of the smaller dams multiply the water supply of a smaller dam,while Bd WS represents the water supply of the Kariba Dam.Besides, the water quality of the multiple-dam system should be greater than the Kariba dam.sd Bd WQ WQ ≥,sd WQ represents the expected average water quality of the Lake Kariba if the authority adoptthe option three, while Bd WQ represents the present water quality of the Lake Kariba.5.2 Joint Operation of Dam System ModelJoint operation of dam system can utilize the differences between dam capacity and hydrologic condition, so that we develop a joint compensation effect for the dam group and make full use of water resources. Compared with the traditional single large dam, the dam group establish on the basis of multi –dam system, which could help us take advantage of water resources for our social benefits, including economic and social benefits. Therefore, it is necessary to establish an effective water resources dispatching scheme.In order to better express our model ,we let 1...i n =indicates the number of dams , 1...j T =denotes the cycle of water dispatching ,ij V illustrates the th i dam ’s water storage during theth j period.[5]The ObjectiveThe hydropower station mainly bring about economic and social benefits. But obviously, hydropower station can bring magnificent economic benefits. Among them, the most direct indication is the dam power generation. Therefore, taking the reservoir power generation as the revelation of economic benefit.11***n Te i ij ij i j I K q H t ===∆∑∑ij q is the discharge flow of the th i dam in the th j period ,ij H is the hydraulic head of th i dam in the th j period ,i K is the force-voltage factor of the th i dam ,t ∆is the time period.In addition to creating enormous economic benefits, a large dam can also bring huge social benefits. Through the construction of dams, it can meet the need of a large number of industrial and agricultural water, also the domestic water.11()n Ts ij ij i i I S D ===-∑∑ij S is the actual water supply th i dam in the th t stage ,ij D is water demand or planned water supply of the th i dam in the th t stage.Therefore, we should make full use of water resources so as to make the economic and social benefits as large as possible.[6]max()e s I I I =+The Constraints● Water Balance,(1)()i t it it it it V V Q q t L +=+-⋅∆-,(1)(1),i t i t it Q q QJ +-=+it Q 、ij q are the average inflow into the dam and discharge volume in the th t period of the th i dam,it L is the evaporation and leakage loss.it QJ is the runoff volume between the th i dam and the th j dam.● Capacity of the DamTo prevent floods and droughts ,The capacity of each dam must be limited.min max i it i V V V ≤≤min i V 、max i V are the upper and lower limit of the th i dam’s water storage ,namely the dead capacity and the flood control capacity.● Discharge Flow ConstraintIn order to keep the normal life standard and to maintain the downstream ecological water use, we must ensure the certain discharge of water, we employ min i q to indicate the minimal discharge of water. Because of the limitation of the dam itself and the purpose of flood control, there need to be a maximal discharge capacity constraint max i qm max i it i q in q q ≤≤In conclusion, in order to make economic benefit and social benefit as large as possible while satisfying the constraint conditions, we need to develop water resources optimized dispatching scheme.1111max ***()n T n Ti ij ij ij ij i j i i I K q H t S D =====∆+-∑∑∑∑,(1),(1)(1),()*..min max m max i t it it it iti t i t it i it i i it i V V Q q t L Q q QJ s t V V V q in q q ++-=+-∆-⎧⎪=+⎪⎨≤≤⎪⎪≤≤⎩it V 、it q are the interval-type variable ,min i V 、min i q correspond to meet the basic industrial and agricultural water 、domestic water and ecological water ,they are the dead water level. For safety considerations such as flood control ,max i V 、max i q are the maximal water level. We let [,]i i Vf VF to be the of it V ,[,]i i qf qF is the optimum interval of it q .[7]1()/(min ),min 1,1()/(max ),max 0,i it i i i it ii it i it it i i i i it iVf V Vf V V V Vf Vf V VF V VF V VF VF V V else λ---≤≤⎧⎪≤≤⎪=⎨---≤≤⎪⎪⎩ 11N t it i N λλ==∑ 1()/(min ),min 1,1()/(max ),max 0,i it i i i it ii it i it it i i i i it i qf q qf q q q qf qf q qF q qF q qF qF q q else μ---≤≤⎧⎪≤≤⎪=⎨---≤≤⎪⎪⎩ 11N t it i N μμ==∑ 6 Model Implementation and Results6.1 The Number and LocationMeasuring the demand of the nearby cityTOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is a commonly used and effective method in multi-objective decision analysis. Hence ,we employ this model and then investigate extended TOPSIS to evaluate the demand of electricity and water of each city.Then we use the data to calculate the demand of the electricity and water with TOPSIS, and part of the results is shown in Table 1.Table 1 The Demand of Electricity and WaterCalculate the shortest distance from each dam to each cityThe dam should be built in the valley of the river fully, because the project is small with low cost. Moreover, the construction of small dams is mainly to replace the larger dam, so the small dam should be constructed mainly in the downstream of the Kariba dam in the canyon. Figure 1 is the suitable site for building dams.Figure 1 The Suitable Gorge for Building DamsWith respect to the option 3 that we need to construct 10 to 20 small dams, considering the geological factors around the dam, we first select the suitable location of the 20 dams.According to our model, we use the distance from the dam to the center of the city as a representative of the distance to the city. A total of 25 cities are selected close to the Kariba gorge, including 15 cities in Zambia, 10 cities in Zimbabwe. We search and calculate the shortest distance and path of each dam to the city through Google maps, and the results of some small dams to the cities are shown in Table 2.Table 2 The Distance Between the Dams and the City(Part)● The Data of Other FactorsAt the same time, we collect the data of other related factors through the Zambia National Bureau of Statistics, the World Bank, the World Commission on Dams and other institutions to gain the relevant statistics.Table 3 The Data of Other FactorsDWL NWL FWL BFWL RLI WS WQ Kariba 475.5 484.6 490 476.7 9000 608.5 19 Multiple 382 408 412 385 1n sd i i R=∑ e WS n ⋅ e WQUnder normal circumstances the water level should be higher than the dead water level, and lower than the normal position. But before the flood season, the water level is lower than the limit of water level.● The numbers and the locationThis optimal problem belongs to the NP-hard problem. We can’t solve it in polynomial time. So we can only use heuristic algorithms such as artificial neural networks, genetic algorithm, simulated annealing to obtain the approximate solution. In this paper, we select the genetic algorithm to solve the problem.We run the program repeatedly, and finally get a relatively good result and determine our number and location of the dams. There should be 12 smaller dams in the Kariba Gorge. Besides, we select the optimal 12 dam location to maximize our objective function from 20 appropriatedam sites. The sixth and twelfth site locations are listed in the Table 4Table 4 The Location of the DamAt the same time, we will also mark the location of the small dam on the map, we put the location of the sixth and twelfth dam on the map. We can see it on the Figure 2 andFigure 3Figure 2 The Location of the 6th Dam Figure 3 The Location of the 12th Dam 6.2 The Strategy of Modulating Water FlowTraditional optimization algorithm mostly belongs to the convex optimization category. It demands a unique global optimal solution, which is often used in practical applications. A number of heuristic intelligent algorithm, for example genetic algorithm etc.These methods show that the algorithm can work out satisfactory results for solving the optimization problem. Employing joint operation of dam system model, we use genetic algorithm and Matlab2014 for the solution.[8]By running the genetic algorithm and adjusting the parameters, we obtain a relatively satisfactory result, and then develop a joint operation of dam system model.(The picture of the results is shown in the appendix part four.)Normal Flow Year:Take the climate and hydrological conditions of the average of nearly5 years to simulate normal climatic conditions.In normal years, the water resources dispatching of the dam system shows obvious seasonal difference. In the dry season from June to September, the discharge of each reservoir reaches the bottom line. Compared with the middle and lower reaches of the river, upper and middlereaches of water resources and reserves are relatively abundant, therefore, still a lot of water could be scheduled downstream. But until the rainy season from November to March, the precipitation intensity and the discharge of each dam are very large. The results show that the discharge index and storage capacity index perform better in May and October, which are in the optimum range, while the other month are all above 0.7, this is a satisfactory result.●Low Flow Year: The monthly precipitation is taken as the highest value in the past 30years, simulating the more serious flood threat..When the annual precipitation decreases, each dam discharge is significantly lower, but the discharge index and the capacity index is still above 0.7, which reflects the joint operation of dam system still has obvious effect to resist abnormal weather like the drought condition.●High Flow Year:The monthly precipitation is taken as the highest value inthe past 30years, simulating the more serious flood threat.When the annual precipitation has increased significantly, then the reservoir’s discharge would increase. While the discharge of the rainy season increases a lot, but in dry season the increase range is smaller, which makes the discharge capacity index and volume index increase significantly from May to September. Although the index decreases significantly in November and February the figure are more than 0.7, is still relatively satisfactory.●Differentiation Year:The precipitation from May to September is taken as the lowestvalue in the past 30 years, the precipitation from October to April was taken as the highest value in the past 30 years. So that we could simulate drought, flood significantly differentiated condition..When confronted with the differentiation year where there comes rainy season when the precipitation increases and the dry season when the precipitation decreases all come about in one year. The discharge flow of each reservoir expands seasonally, which makes the discharge index and storage capacity index of each month decrease, and it is more obvious in the rainy season. Which can not be ignored is that the discharge flow indicators and storage capacity indicators remained at 0.7 or more.[9]7. Sensitivity Analysis7.1 The Model of Determination of the Number and Location●Remove an important city of both countriesIn the questions we discussed above,we have selected 15 cities in Zambia,10 cities in Zimbabwe to specify the number and placement of the newly built smaller dams. Among the sensitivity analysis, we remove important cities of the two countries, thus, we could see whether this movement would influence the number and placement of constructing dams.In our analysis, we leave out Lusaka (The capital city of Zambia) and Harare(The capital city of Zimbabwe) from our original cities, yet, we still use the multi objective optimization model and genetic algorithm we already established to calculate the number and placement of smaller dams. We discover that the optimal number of constructing dams is also 12, but the location of each dam is slightly changed. Just the fourth and the eleventh dam’s place changes a lot, while other dam’s place just changes a little. Therefore, we list the location of the fourth and the eleventh dam’s site in Table 5.。