Research on Network Maintenance Strategy Selection Based on Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution Algorithm

Network maintenance strategy selection is a multi-objective decision making topic. It mostly depends on the uncertainty and fuzziness of decision makers and conditions. In this paper, based on analytic hierarchy process(AHP) and technique for order preference by similarity to ideal solution(TOPSIS), TOPSIS partial order method is proposed to choose the optimal maintenance strategy. This method uses AHP to determine the weights of evaluation indexes. The optimal maintenance strategy choice is given as an example to demonstrate the effectiveness of the method.

基于组合赋权-TOPSIS模型的机场运行效率评价

为提高机场运行效率评价结果的科学性和全面性,提出了一种基于组合赋权-TOPSIS(technique for order performance by similarity to ideal solution)模型的机场运行效率评价方法。从机位运行效率、旅客登机效率、飞机滑行效率和协同效率4个维度出发,构建了由航班靠桥率、廊桥周转率、机位变更比例等11个指标组成的机场运行效率评价体系;利用G1法、熵权法分别计算评价指标主观和客观权重,以最小化主客观加权属性偏离程度为目标计算组合权重;使用TOPSIS计算待评价机场综合评价指数。利用该模型分析国内3类共8家机场的运行效率,可以得到各评价对象的运行效率等级和综合排名。结果表明:该模型能够有效探明影响机场运行效率的主要因素,具有一定的参考价值。

Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

Target-tracked prioritization to surveille ballistic missiles

The missile-tracked priority assessment for the early warning system monitoring multi-missile very well, is the first task to defend them and useful to perform optimally the sensor-to-missile assignment. The problem of the missile-tracked priority assessment is of incomplete information, of multi-attribute and dynamic. To solve the dificult problem, the index system, which includes six classification indices, is established by means of reducing the target＇s primary information which the early warning system focuses on. The lack of some attributes values, which is caused by the incomplete information, is handled by the approach： first classifying each attribute as unknown one or known one, and then subdividing the latter, last using the expectation and the information entropy if the attribute is known but uncertain. With a view of reality, nine qualitative evaluation criteria are given. Based on them each index is quantified by the eigenvector method. And then based on the improved technique for order preference by similarity to ideal solution （TOPSIS）, the targets-tracked priorities are assessed and sorted by an evaluation function from three aspects： 1） the quantity of the available information, 2） the affirmative or accurate degree of the available information, 3） the classification or trait of the available information.

TOPSIS with Belief Structure for Group Belief Multiple Criteria Decision Making

The technique for order performance by similarity to ideal solution （TOPSIS） is one of the major techniques in dealing with multiple criteria decision making （MCDM） problems, and the belief structure （BS） model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers＇ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.

An Integrated Framework for Cloud Service Selection Based on BOM and TOPSIS

Many businesses have experienced difficulties in selecting a cloud service provider(CSP)due to the rapid advancement of cloud computing services and the proliferation of CSPs.Many independent criteria should be considered when evaluating the services provided by different CSPs.It is a case of multi-criteria decision-making(MCDM).This paper presents an integrated MCDM cloud service selection framework for determining the most appropriate service provider based on the best only method(BOM)and technique for order of preference by similarity to ideal solution(TOPSIS).To obtain the weights of criteria and the relative importance of CSPs based on each criterion,BOM performs pairwise comparisons of criteria and also for alternatives on each criterion,and TOPSIS uses these weights to rank cloud alternatives.An evaluation and validation of the proposed framework have been carried out through a use-case model to prove its efficiency and accuracy.Moreover,the developed framework was compared with the analytical hierarchical process(AHP),a popular MCDM approach,based on two perspectives:efficiency and consistency.According to the research results,the proposed framework only requires 25%of the comparisons needed for the AHP approach.Furthermore,the proposed framework has a CR of 0%,whereas AHP has 38%.Thus,the proposed framework performs better than AHPwhen it comes to computation complexity and consistency,implying that it is more efficient and trustworthy.

面向自愈的智能配电网免疫力评估方法

自愈是智能配电网区别于传统配电网的显著特征,为提高各项自愈技术实用化水平,需要准确掌握智能配电网整体免疫力水平。因此,借鉴人体免疫系统机理,提出了智能配电网免疫系统,包括免疫耐受、免疫自稳、免疫识别、免疫应答和免疫恢复5类功能,在此基础上,提出了基于改进层次分析法与逼近理想解距离法相结合的智能配电网免疫力评估模型构建方法,并构建了智能配电网免疫力评估指标体系以及智能配电网免疫力评估模型。此评估模型能够全面且多层次地考虑影响智能配电网免疫力强弱的各类因素,在实际应用中为智能配电网精细化运维检修和管理提供理论参考。

基于模糊群决策的绿色供应商选择和订单分配方法

随着市场竞争愈发激烈、全球环境日益恶化以及公众环保意识的提高,绿色采购问题受到了广泛关注。现有研究绝大多数聚焦于考虑绿色准则的供应商选择问题,以实现可持续经营。然而,在综合考虑时间、价格和成本等因素的前提下,从适应性强的供应商处获得适当的产品,对于企业来说更为可行和经济,即供应商选择和订单分配。为了解决上述关键问题,提出了一种模糊环境下的多准则群体决策方法。提出了一种基于理想解相似性偏好排序和层次分析法(technique for order of preference by similarity to ideal solution and analytic hierarchy process,TOPSIS-AHP)的模糊排序方法,该方法可根据企业战略灵活调整传统准则和绿色准则的权重。在双目标优化模型中引入供应商排名进行订货,在实现采购绩效最大化的同时,最大限度地降低采购成本。结果表明:所提方法能够有效评价供应商绩效,并优化候选供应商之间的订单分配。

Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

Optimizing Rank of Landscape Planning Works of Urban Wetland Park

Classifying and ranking the huge amounts of landscape planning works of urban wetland park is always difficult due to the multi-functions （ecological, leisure, educational and disaster prevention） of the urban wetland park. Therefore, an optimizing rank system is urgently needed. Analytic Hierarchy Process （AHP） and Technique for Order Preference by Similarity to Ideal Solution （TOPSIS） models were used to rank the planning works of 30 urban wetland park based on four mainly factors, which included landscape ecological planning, landscape planning, ecological planning and economic planning. The study indicated that the AHP- TOPSIS model had good discrimination in the classification and ranking of landscape planning works of urban wetland park and it was also applicable to the planning works of other urban greenbelts.

Vertical Handover Decision for Mobile IoT Edge Gateway Using Multi-Criteria and Fuzzy Logic Techniques

Internet of Things (IoT) is ubiquitous, including objects or devices communicating through heterogenous wireless networks. One of the major challenges in mobile IoT is an efficient vertical handover decision (VHD) technique between heterogenous networks for seamless connectivity with constrained resources. The conventional VHD approach is mainly based on received signal strength (RSS). The approach is inefficient for vertical handover, since it always selects the target network with the strongest signal without taking into consideration of factors such as quality of service (QoS), cost, delay, etc. In this paper, we present a hybrid approach by integrating the multi-cri- teria based VHD (MCVHD) technique and an algorithm based on fuzzy logic for efficient VHD among Wi-Fi, Radio and Satellite networks. The MCVHD provides a lightweight solution that aims to achieving seamless connectivity for mobile IoT Edge Gateway over a set of heterogeneous networks. The proposed solution is evaluated in real time using a testbed containing real IoT devices. Further, the testbed is integrated with lightweight and efficient software techniques, e.g., microservices, containers, broker, and Edge/Cloud techniques. The experimental results show that the proposed approach is suitable for an IoT environment and it outperforms the conventional RSS Quality based VHD by minimizing handover failures, unnecessary handovers, handover time and cost of service.

Analysis of Supply Chain Sustainability Drivers in the Oil and Gas Industry under Covid-19 Pandemic

The supply chain of many industries,including Oil and Gas,was significantly affected by the disruption caused by the Covid pandemic.This,in turn,had a knock-on effect on other industries around the globe.Sustaining the impact of the disruption posed a major challenge for the industry.This study contributes to the existing literature by identifying and analyzing the most significant drivers that affected the sustainability of the Oil and Gas supply chain during the Covid pandemic.Fifteen drivers were identified based on an extensive literature review and a survey conducted with experts working in the Oil and Gas industry.Multi-criteria decision-making methodologies were used to analyze these drivers.The analysis from the fuzzy analytical hierarchy process found that the most important drivers for the sustainability of the Oil and gas supply chain during the pandemic were"Risk management capacity","Government regulation"and"Health and safety of employees".On the other hand,the driver"Community Pressure"was found to be of the least importance.Furthermore,the study integrated the results of the fuzzy analytical hierarchy process with the fuzzy technique for order of preference by similarity to ideal solution to calculate the supply chain sustainability index.A case example was demonstrated to rank the industries based on such calculations.This study can support the governmental institutions in benchmarking the Oil and Gas industry based on its sustainability index.Additionally,the outcomes of the study will help industrial decision makers prioritize the drivers the company should focus and devise strategies based on the priority to improve the sustainability of their supply chain during severe disruption.This will be crucial as the World health organization has cautioned that the world may encounter another pandemic in the near future.

Emergency management capacity assessment for urban rail transit-an example of Beijing Metro Line 13

In order to improve the emergency management capability of urban rail transit system and reduce accidents during metro operation,an emergency management capability evaluation method combining analytic hierarchy process(AHP)and technique for order preference by similarity to ideal solution(TOPSIS)is proposed.Based on the Prevention Preparation Response Recovery(PPRR)model,factors influencing the emergency management capability of the urban rail transit system are summarized from the perspective of‘human,machine,environment and management’.Then,an emergency management capability evaluation index system containing of 20 secondary indicators is constructed in four stages:emergency prevention,emergency preparation,emergency response and emergency recovery.The weights of indicators are calculated using the AHP method,and the closeness of each indicator to the optimal solution is analysed with the TOPSIS method.Finally,take the Beijing Metro Line 13 as an example to investigate the level of emergency management capability of urban rail transit.The results show that the emergency management capability of Beijing’s urban rail transit system is‘well’,among which hazard prevention measures(0.31)and emergency response team(0.34)have a greater weight on the emergency management capability of rail transit.The model can more accurately assess the emergency management capability of urban rail transit and provide a basis for emergency management.

Comprehensive evaluation factor of optoelectronic properties for transparent conductive metallic mesh films

Finding the optimal optoelectronic properties(zero-order optical transmittance,shielding effectiveness,and stray light uniformity)of metallic mesh is significant for its application in electromagnetic interference shielding areas.However,there are few relevant studies at present.Based on optoelectronic properties,we propose a comprehensive evaluation factor Q,which is simple in form and can be used to evaluate the mesh with different parameters in a simple and efficient way.The effectivity of Q is verified by comparing the trend of Q values with the evaluation results of the technique for order preference by similarity to ideal solution(TOPSIS).The evaluation factor Q can also be extended to evaluate the optoelectronic properties of different kinds of metallic meshes,which makes it extremely favorable for metallic mesh design and application.

Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative:an empirical study of Southeast Asia

Instruction:The countries along the Belt and Road Initiative remain high exposure and vulnerability to climate extremes.Southeast Asia,a significant part of the Belt and Road Initiative,suffers a lot from flood disasters.This study assessed the flood disaster risk from 1990–2015 in all 11 Southeast Asian countries.A model integrating the coefficient of variation approach and the Technique for Order Preference by Similarity to Ideal Solution method was introduced to analyze the flood disaster data.Considering that populations living in areas where elevation is below 5 m and land area where elevation is below 5 m have reached 11.86%and 3.54%(2015),respectively,the two indicators were opted for to propose new metrics for flood disaster risk assessment.Outcomes:Our findings show that the flood disaster risk in Southeast Asia appeared very high during most of the study period.Indonesia had an extremely high flood disaster risk,followed by Vietnam,whereas Laos,Malaysia,Brunei,and Timor Leste had lower flood risks.The model introduced in this paper is quite simple and easy to understand,providing accessible flood risk information for decision makers.Conclusion:The results we obtained have practical implications for land use and investment activities in Southeast Asia.

A hesitant fuzzy linguistic terms set-based AHP-TOPSIS approach to evaluate ERP software packages

Purpose–In this paper,two popular multiple-criteria decision-making(MCDM)methods with hesitant fuzzy logic approach;hesitant fuzzy analytic hierarchy process(hesitant F-AHP)and hesitant fuzzy the technique for order preference by similarity to ideal solution(HF-TOPSIS)are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning(ERP)alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.Design/methodology/approach–Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues(i.e.time loss,increased costs and a loss of market share).On the other hand,finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.Findings–In this integrated approach,the hesitant F-AHP is used to determine the criteria weights,as the hesitant F-TOPSIS is utilized to rank ERP package alternatives.The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.Research limitations/implications–If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers,the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations.Therefore,the number of criteria and alternatives should be at reasonable numbers.Practical implications–The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.Originality/value–Furthermore,in literature,to the best of our knowledge,the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.

Location optimization of multiple distribution centers under fuzzy environment

Locating distribution centers optimally is a crucial and systematic task for decision-makers.Optimally located distribution centers can significantly improve the logistics system's efficiency and reduce its operational costs.However,it is not an easy task to optimize distribution center locations and previous studies focused primarily on location optimization of a single distribution center.With growing logistics demands,multiple distribution centers become necessary to meet customers' requirements,but few studies have tackled the multiple distribution center locations(MDCLs) problem.This paper presents a comprehensive algorithm to address the MDCLs problem.Fuzzy integration and clustering approach using the improved axiomatic fuzzy set(AFS) theory is developed for location clustering based on multiple hierarchical evaluation criteria.Then,technique for order preference by similarity to ideal solution(TOPSIS) is applied for evaluating and selecting the best candidate for each cluster.Sensitivity analysis is also conducted to assess the influence of each criterion in the location planning decision procedure.Results from a case study in Guiyang,China,reveals that the proposed approach developed in this study outperforms other similar algorithms for MDCLs selection.This new method may easily be extended to address location planning of other types of facilities,including hospitals,fire stations and schools.

Application of multi-criteria decision making methods for selection of micro-EDM process parameters

Ti-6A1-4V super alloy is an important engi- neering material with good strength to weight ratio and a wide range of applications in a number of engineering fields because of its excellent physical and mechanical properties. This work determines optimum process parameters such as pulse on time, peak current, gap voltage and flushing pressure, which influence the micro-electro discharge machining （EDM） process during machining of Ti-6AI-4V using combined methods of response surface methodology （RSM） and fuzzy-technique for order pref- erence by similarity to ideal solution （TOPSIS）. Central composite design （CCD） is used in the experimental investigation. A decision making model is developed to identify the optimum process parameters in the micro- EDM process, which influences several machining criteri- ons such as material removal rate （MRR）, tool wear rate （TWR）, overcut （OC） and taper. Triangular fuzzy numbers are used to determine the weighting factor for each process criterion. Further a fuzzy-TOPSIS method is used to select the most desirable factor level combinations. The proposed technique can be used to select optimal process parameters from various sets of combinations of process parameters in a micro-EDM process.

Dynamic partner selection in Cloud Federation for ensuring the quality of service for cloud consumers

Cloud Computing has become the popular paradigm for accessing the various scalable and on-demand computing services over the internet.Nowadays,individual Cloud Service Providers(CSPs)offering specialized services to the customers collaborate to form the Cloud Federation,in order to reap the real benefits of Cloud Computing.By collaboration,the member CSPs of the federation achieve better resource utilization and Quality of Service(QoS),thereby increasing their business prospects.When a CSP runs out of resources in the Cloud Federation,in order to offload the customer requests for resources to other CSP(s),identifying a suitable partner is a challenging task due to the lack of global coordination among them.In this paper,we propose the design and implementation of an efficient partner selection mechanism in the Cloud Federation,using the Analytic Hierarchy Process(AHP)and the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)methods,and also considering the trust values of various CSPs in the federation.The AHP method is used to calculate the weights of the QoS parameters used in the TOPSIS method which is used to rank the various CSPs in the Cloud Federation according to the user requirements.Simulation results show the effectiveness of this approach in order to efficiently select the trustworthy partners in large scale federations to ensure the required QoS to the cloud consumers.