A min-max optimization approach for weight determination in analytic hierarchy process

A min-max optimization method is proposed as a new approach to deal with the weight determination problem in the context of the analytic hierarchy process. The priority is obtained through minimizing the maximal absolute difference between the weight vector obtained from each column and the ideal weight vector. By transformation, the. constrained min- max optimization problem is converted to a linear programming problem, which can be solved using either the simplex method or the interior method. The Karush-Kuhn- Tucker condition is also analytically provided. These control thresholds provide a straightforward indication of inconsistency of the pairwise comparison matrix. Numerical computations for several case studies are conducted to compare the performance of the proposed method with three existing methods. This observation illustrates that the min-max method controls maximum deviation and gives more weight to non- dominate factors.

Marginal optimization method to improve the inconsistent comparison matrix in the analytic hierarchy process

To improve the inconsistency in the analytic hierarchy process(AHP), a new method based on marginal optimization theory is proposed. During the improving process, this paper regards the reduction of consistency ratio(CR) as benefit, and the maximum modification compared to the original pairwise comparison matrix(PCM) as cost, then the improvement of consistency is transformed to a benefit/cost analysis problem. According to the maximal marginal effect principle, the elements of PCM are modified by a fixed increment(or decrement) step by step till the consistency ratio becomes acceptable, which can ensure minimum adjustment to the original PCM so that the decision makers’ judgment is preserved as much as possible. The correctness of the proposed method is proved mathematically by theorem. Firstly, the marginal benefit/cost ratio is calculated for each single element of the PCM when it has been modified by a fixed increment(or decrement).Then, modification to the element with the maximum marginal benefit/cost ratio is accepted. Next, the marginal benefit/cost ratio is calculated again upon the revised matrix, and followed by choosing the modification to the element with the maximum marginal benefit/cost ratio. The process of calculating marginal effect and choosing the best modified element is repeated for each revised matrix till acceptable consistency is reached, i.e., CR<0.1. Finally,illustrative examples show the proposed method is more effective and better in preserving the original comparison information than existing methods.

Multiobjective optimal dispatch of microgrid based on analytic hierarchy process and quantum particle swarm optimization

Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispatch model is developed for a standalone MG composed of wind turbines,photovoltaics,diesel engine unit,load,and battery energy storage system.The economic cost,environmental concerns,and power supply consistency are expressed via subobjectives with varying priorities.Then,the analytic hierarchy process algorithm is employed to reasonably specify the weight coefficients of the subobjectives.The quantum particle swarm optimization algorithm is thereafter employed as a solution to achieve optimal dispatch of the MG.Finally,the validity of the proposed model and solution methodology are con firmed by case studies.This study provides refere nee for mathematical model of multiojective optimizati on of MG and can be widely used in current research field.

Energy retrofit and conservation of a historic building using multi-objective optimization and an analytic hierarchy process

When deciding on the best historic building retrofit,energy savings and thermal comfort can be quantitatively evaluated using an energy model,whereas conservation compatibility is intrinsically qualitative and reflects the perspective of the local heritage authority. We present a methodology that permits finding and comparing optimal retrofits for historic buildings in a multi-perspective and quantitative way. We use an analytic hierarchyprocess to quantify conservation compatibility by distilling a conservation score from the opinions of 10 experts in the field. This score,along with energy needs for heating and cooling and thermal comfort,are the three targets of a multi-objective optimization aimed at identifying optimal retrofits for a medieval building in the north of Italy,destined to become a museum. Retrofit measures considered were different kinds of external and internal envelope insulation,improvement of airtightness,replacement of windows,and ventilative cooling. The result is a portfolio of optimal retrofits that cover the whole range of conservation compatibility. We showthat in the analyzed case heritage preservation is compatible with a four-fold reduction in energy needs at a high thermal comfort level. Even higher energy savings are only achievable at the cost of heritage degradation.

Evaluation and Optimization of the Logistics Service of Agricultural Products:an Empirical Analysis Based on Analytic Hierarchy Process

This research,from the theories of management science,supply chain management and logistics engineering,on the basis of extensive investigations,and using the method of analytic hierarchy process(AHP),evaluates the present situation of logistics service of agricultural products.Taking Nanping City(Nanping)as a case,it explores the obstacles existing in current logistics service system and the factors limiting the development of agricultural product logistics service.Combining with the theory of modern logistics system,it reveals the problems in the logistics system and the causes,and then constructs the strategy of optimization for agricultural product logistics service in Nanping.The conclusion of the study can be references for the government to make scientific strategies for the development of the agricultural product logistics service and help logistics enterprises improve their service level.

Stock-Selection Strategies Optimization of Fund Management Companies by Analytic Hierarchy Process

Securities investment fund is one of the most important institutional investors in the securities market. The quality of the management of the securities investment fund by the fund management company not only directly affects its survival and development,but also plays a decisive role in the stable operation of securities market and even the macroeconomy. As China is in rapid development of funds,scientific and effective investment strategies will be the only road for the long-term development of wellestablished fund management companies. We attempt to combine the value investment strategies with quantitative investment strategies to build a system of optimized investment strategies with the use of analytic hierarchy process so as to improve business performance of fund management companies and to foster the concept of value investment. Moreover,it possesses certain significance in enriching investment strategies for securities investment fund and promoting the healthy growth of the Chinese securities investment fund.

A Genetic Fuzzy Analytical Hierarchy Process Based Projection Pursuit Method for Selecting Schemes of Water Transportation Projects

The optimal selection of schemes of water transportation projects is a process of choosing a relatively optimal scheme from a number of schemes of water transportation programming and management projects, which is of importance in both theory and practice in water resource systems engineering. In order to achieve consistency and eliminate the dimensions of fuzzy qualitative and fuzzy quantitative evaluation indexes, to determine the weights of the indexes objectively, and to increase the differences among the comprehensive evaluation index values of water transportation project schemes, a projection pursuit method, named FPRM-PP for short, was developed in this work for selecting the optimal water transportation project scheme based on the fuzzy preference relation matrix. The research results show that FPRM-PP is intuitive and practical, the correction range of the fuzzy rained is both stable and accurate; preference relation matrix A it produces is relatively small, and the result obtherefore FPRM-PP can be widely used in the optimal selection of different multi-factor decision-making schemes.

Using Extension Theory and Fuzzy Analytic Hierarchy Process on Heterogeneous Wireless Network Selection Algorithm

In order to solve the problem that determining decision factors weights is of subjectivity in heterogeneous wireless network selection algorithm, a network selection algorithm based on extension theory and fuzzy analytic hierarchy process （FAHP） is proposed in this paper. In addition, user and operator codetermine the optimal network using the proposed algorithm, which can give consideration to user and operator benefits. The fuzzy judgment matrix is coustructed by membership degree of decision factors which is calculated according to extension theory. The comprehensive weight of each decision factor is obtained using FAHP. Finally, the optimal network is selected through total property value ranldng of each candidate network under user preference and operator preference. The simulation results show that the proposed algorithm can select the optimal network efficiently and accurately, satisfy user preference, and implement load balance between networks.

Research on Optimal Design of Campus Space Based on POE Concept: A Case Study of Anhui Xinhua College

Through the analysis of the overall landscape,revetments and roads and plant landscape,10 evaluation factors were determined.The comprehensive evaluation model for the campus space of Anhui Xinhua University was constructed by analytic hierarchy process(AHP).The results showed that revetment safety,road convenience,plant disease resistance and campus activity space were important factors affecting the spatial form planning of campus.Through the comparative analysis of the collected data,optimization suggestions were put forward to provide a basis for the establishment of“people-oriented”campus open space system.

An Experimental Investigation into the Amalgamated Al2O3-40% TiO2 Atmospheric Plasma Spray Coating Process on EN24 Substrate and Parameter Optimization Using TLBO

Surface coating is a critical procedure in the case of maintenance engineering. Ceramic coating of the wear areas is of the best practice which substantially enhances the Mean Time between Failure (MTBF). EN24 is a commercial grade alloy which is used for various industrial applications like sleeves, nuts, bolts, shafts, etc. EN24 is having comparatively low corrosion resistance, and ceramic coating of the wear and corroding areas of such parts is a best followed practice which highly improves the frequent failures. The coating quality mainly depends on the coating thickness, surface roughness and coating hardness which finally decides the operability. This paper describes an experimental investigation to effectively optimize the Atmospheric Plasma Spray process input parameters of Al2O3-40% TiO2 coatings to get the best quality of coating on EN24 alloy steel substrate. The experiments are conducted with an Orthogonal Array (OA) design of experiments (DoE). In the current experiment, critical input parameters are considered and some of the vital output parameters are monitored accordingly and separate mathematical models are generated using regression analysis. The Analytic Hierarchy Process (AHP) method is used to generate weights for the individual objective functions and based on that, a combined objective function is made. An advanced optimization method, Teaching-Learning-Based Optimization algorithm (TLBO), is practically utilized to the combined objective function to optimize the values of input parameters to get the best output parameters. Confirmation tests are also conducted and their output results are compared with predicted values obtained through mathematical models. The dominating effects of Al2O3-40% TiO2 spray parameters on output parameters: surface roughness, coating thickness and coating hardness are discussed in detail. It is concluded that the input parameters variation directly affects the characteristics of output parameters and any number of input as well as output parameters can be easily optimized using the current approach.

Configuration optimization model of multi-energy distributed generation system

To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model mainly consists of two parts, the determination of initial configuration schemes according to user preference and the selection of the optimal scheme. The comprehensive evaluation index（CEI）, which is acquired through the analytic hierarchy process（AHP） weight calculation method, is adopted as the evaluation criterion to rank the initial schemes. The optimal scheme is obtained according to the ranking results. The proposed model takes the diversity of different equipment parameters and investment cost into consideration and can give relatively suitable and economical suggestions for system configuration.Additionally, unlike Homer Pro, the proposed model considers the complementation of different renewable energy resources, and thus the rationality of the multi-energy DG system is improved compared with the single evaluation criterion method which only considers the total cost.

Evaluation and optimization of secondary water supply system renovation

Due to pollution in second water supply system (SWSS),nine renovation alternative plans were proposed and com-prehensive evaluations of different plan based on Analytical Hierarchy Process (AHP) were presented in this paper. Comparisons of advantages and disadvantages among the plans of SWSS renovations provided solid foundation for selecting the most appro-priate plan for engineering projects. In addition,a mathematical model of the optimal combination of renovation plans has been set up and software Lingo was used to solve the model. As a case study,the paper analyzed 15 buildings in Tianjin City. After simulation of the SWSS renovation system,an optimal scheme was obtained,the result of which indicates that 10 out of those 15 buildings need be renovated in priority. The renovation plans selected for each building are the ones ranked higher in the com-prehensive analysis. The analysis revealed that the optimal scheme,compared with two other randomly calculated ones,increased the percentage of service population by 19.6% and 13.6% respectively,which significantly improved social and economical benefits.

Enabling a Viable Technique for the Optimization of LNG Carrier Cargo Operations

In this study, we optimize the loading and discharging operations of the Liquefied Natural Gas(LNG) carrier. First, we identify the required precautions for LNG carrier cargo operations. Next, we prioritize these precautions using the analytic hierarchy process(AHP) and experts' judgments, in order to optimize the operational loading and discharging exercises of the LNG carrier, prevent system failure and human error, and reduce the risk of marine accidents. Thus, the objective of our study is to increase the level of safety during cargo operations.

Lectotype optimization of mid-highrise residential building based on site conditions and seismic fortification intensity

A multi-objective lectotype optimization model based on site conditions and seismic fortification intensity is presented for mid-highrise residential buildings taking into account multiple items such as the original investment, disaster losses and maintenance cost, the integral stiffness, the total ductility, the construction period, and so on. A Three-Scale Fuzzy Analytical Hierarchy process is proposed by introducing the Three-Scale Analytical Hierarchy process and the trapezoid fuzzy number. The result of a calculation example shows that the T-FAHP is practical.

Parameter Optimization of Amalgamated Al2O3-40% TiO2 Atmospheric Plasma Spray Coating on SS304 Substrate Using TLBO Algorithm

SS304 is a commercial grade stainless steel which is used for various engineering applications like shafts, guides, jigs, fixtures, etc. Ceramic coating of the wear areas of such parts is a regular practice which significantly enhances the Mean Time Between Failure (MTBF). The final coating quality depends mainly on the coating thickness, surface roughness and hardness which ultimately decides the life. This paper presents an experimental study to effectively optimize the Atmospheric Plasma Spray (APS) process input parameters of Al2O3-40% TiO2 ceramic coatings to get the best quality of coating on commercial SS304 substrate. The experiments are conducted with a three-level L18 Orthogonal Array (OA) Design of Experiments (DoE). Critical input parameters considered are: spray nozzle distance, substrate rotating speed, current of the arc, carrier gas flow and coating powder flow rate. The surface roughness, coating thickness and hardness are considered as the output parameters. Mathematical models are generated using regression analysis for individual output parameters. The Analytic Hierarchy Process (AHP) method is applied to generate weights for the individual objective functions and a combined objective function is generated. An advanced optimization method, Teaching-Learning-Based Optimization algorithm (TLBO), is applied to the combined objective function to optimize the values of input parameters to get the best output parameters and confirmation tests are conducted based on that. The significant effects of spray parameters on surface roughness, coating thickness and coating hardness are studied in detail.

Multi-Criteria Decision Analysis for Usage Based Optimization of Powertrains

The electrification of powertrains leads to an increasing diversification of powertrain configurations. Each single configuration has its specific advantages which appear depending on the usage profile. To find the usage based optimal powertrain in consideration of a variety of evaluation criteria, the powertrains have to be optimized for the usage profile and characteristics have to be extracted from the usage profile. The carbon dioxide emissions of the optimized powertrains and usage based criteria are used in a multi-criteria decision analysis to determine the optimal powertrain for a specific usage profile. The description of characteristic maps forms the objective function of a minimization problem. The determined carbon dioxide emissions are one criterion in a multi-criteria decision process. All considered criteria are at least partly objective so that subjective ratings are eliminated as far as possible. The result is an optimized powertrain for a desired usage under the consideration of objective criteria that are extracted from the usage profile.

考虑碳排放的分布式电源优化配置

对分布式电源接入配电网进行合理的优化配置,能在兼顾运营商和用户利益的同时,改善系统整体电压分布。建立了综合考虑分布式电源投资成本、用户购电成本、网损费用和碳排放费用的多目标优化模型。利用改进层次分析法确定各目标的权重,进而转化为单目标函数规划问题。针对天牛须算法个体单一性在解决高维复杂问题时精度低,优化效果不佳的问题,提出了一种改进天牛须粒子群算法,利用混沌映射对参数进行调整,引入动态惯性权重、莱维飞行机制,提高了收敛速度。以IEEE33节点系统为例,将改进天牛须粒子群算法与粒子群算法及天牛须粒子群算法的效果对比,验证改进算法对分布式电源优化配置问题的可行性,有效降低了碳排放费用、用户购电费用,减少了系统网损,改善了系统整体电压分布。

多场景下基于AHP-EWM的人体健康状态评估模型研究

为解决人体健康评估方法个性化监测不足的问题以及在满足不同场景下健康状态精细化评估的需求,需要一种基于多场景的人体健康状态评估方法来实现长期自动化监测。提出一种基于层次分析法(AHP)和熵权法(EWM)组合的多场景人体健康状态评估模型。首先采集人体在运动、休息、工作/学习和娱乐等4种不同场景下的健康监测指标数据,构建相应的评估指标体系。然后分别根据评估指标计算出AHP和EWM权重,再采用量子粒子群优化(QPSO)算法对AHP和EWM中的主客观权重进行分配,以确保评价指标占比的客观性。最后通过模糊综合评价法对人体健康状态进行评估和量化,并利用实际监测数据对方法的可靠性和稳定性进行验证。实验结果表明,在4种场景下所提方法的综合得分分别为63.78、59.83、58.71和59.21,表明在不同场景下该模型都具有较好的准确性和稳定性。根据评估结果,对测试者的身体状态评价结果进行分析,并给出一些健康建议。所提模型可全面了解人体在不同场景下的健康状况,并为人们提供科学的健康指导,从而为健康管理和疾病预防提供科学依据。

基于AMOWOA的区域综合能源系统运行优化调度

目前,智能优化算法已广泛应用于工程优化中,在当前多能耦合与互补的能源发展趋势下,仅考虑系统经济指标的单目标优化模式已经不再适用于目前区域综合能源系统(Integrated energy system, IES)的运行优化调度,需要研究一种多目标运行策略来解决区域综合能源系统的运行优化调度问题.首先综合考虑经济与能源利用两个指标并结合商业住宅区域的特性,以系统日运行收益和一次能源利用率为优化目标构建商业住宅区域综合能源系统多目标运行优化调度模型.其次由于传统多目标智能优化算法缺乏一种最优解综合评价方法,基于非支配排序以及拥挤度计算的多目标算法框架,提出一种利用模糊一致矩阵选取全局最优解的多目标鲸鱼优化算法(A multi-objective whale optimization algorithm, AMOWOA),并将提出算法对商住区域综合能源系统多目标运行优化调度模型进行求解.最后以华东某商业住宅区域综合能源系统为例进行仿真,验证了该方法的有效性和可行性.

感知价值视角下移动医疗问诊系统设计评价与优化

文章从感知价值视角对移动医疗问诊系统设计进行评价,研究设计要素优先级,探讨优化设计方法。首先,采用层次分析法构建基于感知价值5个维度的移动医疗问诊系统设计评价体系,计算出评价指标的权重和评价公式。其次,依据设计要素的重要性,优化移动医疗问诊系统。最后,通过李克特量表获取30份优化前后两个设计方案的评价数据,对比评价结果。评价数据表明:基于感知价值的设计评价方法具有可行性和有效性,为移动医疗问诊系统指明了设计重点,明确了设计目标。移动问诊系统设计评价体系的建立避免了设计过程的主观性,未来该系统的设计开发可从功能价值、情感价值、效率价值、知识共享价值、信任价值5个维度的设计要素入手,全方位提高用户的感知价值。