预制构件厂精益设计方案评价研究

作为新兴产业，预制构件厂的设计和运营是实现装配式建筑构件高效率、高质量生产和配送的关键前提要素。而精益设计可以帮助预制构件厂从源头消除浪费、提高生产效率，所以对预制构件厂构建精益设计方案并且评价实施后的效果无疑是一个重点问题。针对以上问题，本文从节约资金能力、生产能力、交付能力、持续改进能力等4个视角构建出了预制构件厂精益设计评价指标体系，采用了AHP-DEMATEL法确定了指标的权重，并用改进TOPSIS法得到最终结果，最后以某预制构件厂为例验证了精益设计评价指标体系的合理性和可行性。     

Emergency decision support modeling for COVID-19 based on spherical fuzzy information

Significant emergency measures should be taken until an emergency event occurs. It is understood that the emergency is characterized by limited time and information, harmfulness and uncertainty, and decision-makers are always critically bound by uncertainty and risk. This paper introduces many novel approaches to addressing the emergency situation of COVID-19 under spherical fuzzy environment. Fundamentally, the paper includes six main sections to achieve appropriate and accurate measures to address the situation of emergency decision-making. As the spherical fuzzy set (FS) is a generalized framework of fuzzy structure to handle more uncertainty and ambiguity in decision-making problems (DMPs). First, we discuss basic algebraic operational laws (AOLs) under spherical FS. In addition, elaborate on the deficiency of existing AOLs and present three cases to address the validity of the proposed novel AOLs under spherical fuzzy settings. Second, we present a list of Einstein aggregation operators (AgOp) based on the Einstein norm to aggregate uncertain information in DMPs. Thirdly, we are introducing two techniques to demonstrate the unknown weight of the criteria. Fourthly, we develop extended TOPSIS and Gray relational analysis approaches based on AgOp with unknown weight information of the criteria. In fifth, we design three algorithms to address the uncertainty and ambiguity information in emergency DMPs. Finally, the numerical case study of the novel carnivorous (COVID-19) situation is provided as an application for emergency decision-making based on the proposed three algorithms. Results explore the effectiveness of our proposed methodologies and provide accurate emergency measures to address the global uncertainty of COVID-19.     

Evaluation of suitable locations for the installation of solar thermoelectric power plants

The aim of the present paper is to determine the best location to host a solar thermoelectric power plant. We will seek to show how Geographic Information Systems (GIS) and Multi Criteria Decision Making (MCDM) such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS method) and Analytic Hierarchy Process (AHP), are an excellent combination to solve complex locations problems. The coast of the Region of Murcia in the southeast of Spain has been chosen as the study area to carry out this evaluation.The GIS will be shown to be a very useful tool, since GIS are able to generate a database which serves as a starting point for conducting any decision support system. The posed problem will be resolved using restrictions to reduce the area of study, and the criteria that will influence the decision-making. These criteria will be of different natures; with quantitative criteria (numerical values) coexisting with qualitative criteria (labels and linguistic variables). In this article, AHP will be used to obtain the weights of the criteria, and the fuzzy TOPSIS method for the evaluation of the alternatives. In order to compare the results obtained with TOPSIS, the ELECTRE-TRI methodology will be applied.     

An integrated three-stage maintenance scheduling model for unrelated parallel machines with aging effect and multi-maintenance activities

We propose an integrated three-stage model for maintenance scheduling of unrelated parallel machines (UPMs) with aging effect and multi-maintenance activities (AEMMAs) using a variety of MODM techniques such as the fuzzy analytic hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), and goal programming (GP). We use fuzzy AHP in the first stage of the proposed model to account for the inherent ambiguity and vagueness in real-life maintenance scheduling problems. In the second stage, we use TOPSIS to reduce the multi-objective problem into an efficient bi-objective problem. Finally, we use GP to solve the resulting bi-objective problem and develop an optimal maintenance schedule in the third stage of the model. We use a numerical example to demonstrate the applicability of the proposed approach and exhibit the efficacy of the procedures and algorithms.     

Plant location selection based on fuzzy TOPSIS

The selection of plant location plays a very important role in minimizing cost and maximizing the use of resources for many companies. In this paper, a new TOPSIS approach for selecting plant location under linguistic environments is presented, where the ratings of various alternative locations under various criteria, and the weights of various criteria are assessed in linguistic terms represented by fuzzy numbers. To avoid complicated fuzzy arithmetic operations, the linguistic variables, which are represented by triangular fuzzy numbers, are transformed into crisp numbers based on graded mean representation. The canonical representation of multiplication operations on triangular fuzzy numbers is used to obtain the “positive ideal solution” and the “negative ideal solution”. The closeness efficient is defined to determine the ranking order of all alternatives by calculating the distance to both the “positive-ideal solution” and the “negative-ideal solution” simultaneously. Compared with existing fuzzy TOPSIS methods, the proposed method can deal with group decision-making problems in a more efficient manner. A numerical example of plant location selection is used to illustrate the efficiency of the proposed method.     

An energy‐efficient task‐scheduling algorithm based on a multi‐criteria decision‐making method in cloud computing

The massive growth of cloud computing has led to huge amounts of energy consumption and carbon emissions by a large number of servers. One of the major aspects of cloud computing is its scheduling of many task requests submitted by users. Minimizing energy consumption while ensuring the user's QoS preferences is very important to achieving profit maximization for the cloud service providers and ensuring the user's service level agreement (SLA). Therefore, in addition to implementing user's tasks, cloud data centers should meet the different criteria in applying the cloud resources by considering the multiple requirements of different users. Mapping of user requests to cloud resources for processing in a distributed environment is a well‐known NP‐hard problem. To resolve this problem, this paper proposes an energy‐efficient task‐scheduling algorithm based on best‐worst (BWM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodology. The main objective of this paper is to determine which cloud scheduling solution is more important to select. First, a decision‐making group identify the evaluation criteria. After that, a BWM process is applied to assign the importance weights for each criterion, because the selected criteria have varied importance. Then, TOPSIS uses these weighted criteria as inputs to evaluate and measure the performance of each alternative. The performance of the proposed and existing algorithms is evaluated using several benchmarks in the CloudSim toolkit and statistical testing through ANOVA, where the evaluation metrics include the makespan, energy consumption, and resource utilization.     

基于群决策和投影测度的软件质量评价模型

传统的软件质量评价方法缺少对用户需求的关注,针对这一问题,提出了一种基于用户群体决策的软件质量综合评价模型。首先,这个研究发现,在实数和区间向量空间上,目前的投影测度存在一定的缺陷,为此给出了一个新的标准化投影测度。该模型能综合测度2个向量或矩阵的接近程度,并且允许评价矩阵带有含混的决策信息;其次,将新的投影测度融合在一种改进的TOPSIS技术之中。在此基础上,建立了一个带有实数和区间含混信息的新的群决策方法,并给出算法的伪代码。最后,将该方法应用到软件质量的评价中。该方法侧重于软件用户的需求,综合了用户的群体评价信息,且通过一个软件质量综合评价的实例和实验分析,验证了该方法的有效性和可行性。     

Evaluating the Impact of Software Security Tactics: A Design Perspective

Design architecture is the edifice that strengthens the functionalities as well as the security of web applications. In order to facilitate architectural security from the web application’s design phase itself, practitioners are now adopting the novel mechanism of security tactics. With the intent to conduct a research from the perspective of security tactics, the present study employs a hybrid multi-criteria decision-making approach named fuzzy analytic hierarchy process-technique for order preference by similarity ideal solution (AHP-TOPSIS) method for selecting and assessing multi-criteria decisions. The adopted methodology is a blend of fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity ideal solution (fuzzy TOPSIS). To establish the efficacy of this methodology, the results are obtained after the evaluation have been tested on fifteen different web application projects (Online Quiz competition, Entrance Test, and others) of the Babasaheb Bhimrao Ambedkar University, Lucknow, India. The tabulated outcomes demonstrate that the methodology of the Multi-Level Fuzzy Hybrid system is highly effective in providing accurate estimation for strengthening the security of web applications. The proposed study will help experts and developers in developing and managing security from any web application design phase for better accuracy and higher security.     

基于ANP和TOPSIS优化方法的专业性购物网站评价研究

目的针对专业性购物网站设计的评价排序问题,提出一种基于用户体验的评价方法,并对评价结果数据的处理方法进行研究。方法基于用户体验对专业性购物网站建立评价体系,采用优化的层次分析法(AHP),即网络分析法(ANP)对评价体系的权重进行确立,并引入相对熵优化的TOPSIS方法对网站的评价结果数据进行排序。结论通过样例证明,该评价体系考虑全面,数据处理方法稳定,可以确定专业性购物网站设计和改进中需要优先考虑的问题,并有效且正确地反映市场的实际竞争情况。     

区间复模糊软集的距离测度及其应用

基于区间复模糊软集的概念,定义了多种区间复模糊软集的距离测度公式,包含Hausdorff距离、Hamming距离、Euclidean距离、广义Hausdorff距离、广义Euclidean距离、广义加权Hausdorff距离、广义加权Euclidean距离、加权Hausdorff距离、加权Hamming距离、加权Euclidean距离。提出了除交、并、补运算外的区间复模糊软集的加法、乘法、部分隶属度和部分非隶属度运算以及距离测度之间的运算性质。基于区间复模糊软集距离测度构造了一种TOPSIS决策方法,并将这种决策方法应用于经济分析中,验证了所提方法的可行性。