A software trustworthiness evaluation methodology for cloud services with picture fuzzy information
Author: 
Chuan YueAuthors Info & Claims
Chuan YueAuthors Info & ClaimsGraphical abstract
Display Omitted
References
[1]
Singh S., Sidhu J., Compliance-based multi-dimensional trust evaluation system for determining trustworthiness of cloud service providers, Future Gener. Comput. Syst. 67 (2017) 109–132.
[2]
Basili V.R., Donzelli P., Asgari S., A unified model of dependability: Capturing dependability in context, IEEE Softw. 21 (6) (2004) 19–25.
[3]
Becker S., Hasselbring W., Paul A., et al., Trustworthy software systems: A discussion of basic concepts and terminology, ACM Sigsoft Softw. Eng. Notes 31 (6) (2006) 1–18.
[4]
Yue C., Huang R., Towey D., Xian Z., Wu G., An entropy-based group decision-making approach for software quality evaluation, Expert Syst. Appl. 238 (2024),.
[5]
Yue Z., TOPSIS-based group decision-making methodology in intuitionistic fuzzy setting, Inform. Sci. 277 (2014) 141–153.
[6]
Opricovic S., Tzeng G.-H., Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European J. Oper. Res. 156 (2) (2004) 445–455.
[7]
Zadeh L., Fuzzy sets, Inf. Control 8 (3) (1965) 338–353.
[8]
Atanassov K., Intuitionistic fuzzy sets, Fuzzy Sets and Systems 20 (1) (1986) 87–96.
[9]
Cuong B.C., Picture fuzzy sets, J. Comput. Sci. Cybern. 30 (4) (2014) 409–420.
[10]
Yue Z., Approach to group decision making based on determining the weights of experts by using projection method, Appl. Math. Model. 36 (7) (2012) 2900–2910.
[11]
Yue C., An intuitionistic fuzzy projection-based approach and application to software quality evaluation, Soft Comput. 24 (2020) 429–433.
[12]
Yue Z., Deriving decision maker’s weights based on distance measure for interval-valued intuitionistic fuzzy group decision making, Expert Syst. Appl. 38 (9) (2011) 11665–11670.
[13]
Yue Z., Extension of TOPSIS to determine weight of decision maker for group decision making problems with uncertain information, Expert Syst. Appl. 39 (7) (2012) 6343–6350.
[14]
Shannon C.E., Weaver W., The Mathematical Theory of Communication, University of Illinois press, Urbana, 1947.
[15]
Ji Y., Huang G.H., Sun W., Risk assessment of hydropower stations through an integrated fuzzy entropy-weight multiple criteria decision making method: A case study of the Xiangxi River, Expert Syst. Appl. 42 (12) (2015) 5380–5389.
[16]
Delgado A., Romero I., Environmental conflict analysis using an integrated grey clustering and entropy-weight method: A case study of a mining project in Peru, Environ. Model. Softw. 77 (2016) 108–121.
[17]
Chen T.-Y., A novel VIKOR method with an application to multiple criteria decision analysis for hospital-based post-acute care within a highly complex uncertain environment, Neural Comput. Appl. 31 (2019) 3969–3999.
[18]
Sellak H., Ouhbi B., Frikh B., Palomares I., Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support, Renew. Sustain. Energy Rev. 80 (2017) 1544–1577.
[19]
Quesada F.J., Palomares I., Martínez L., Managing experts behavior in large-scale consensus reaching processes with uninorm aggregation operators, Appl. Soft Comput. 35 (2015) 873–887.
[20]
Ploskas N., Papathanasiou J., A decision support system for multiple criteria alternative ranking using TOPSIS and VIKOR in fuzzy and nonfuzzy environments, Fuzzy Sets and Systems 377 (2019) 1–30.
[21]
Büyüközkan G., Göçer F., Karabulut Y., A new group decision making approach with IF AHP and IF VIKOR for selecting hazardous waste carriers, Measurement 134 (2019) 66–82.
[22]
Çalı S., Balaman Ş.Y., A novel outranking based multi criteria group decision making methodology integrating ELECTRE and VIKOR under intuitionistic fuzzy environment, Expert Syst. Appl. 119 (2019) 36–50.
[23]
Gupta P., Mehlawat M.K., Grover N., Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method, Inform. Sci. 370 (2016) 184–203.
[24]
Chen T.-Y., Remoteness index-based Pythagorean fuzzy VIKOR methods with a generalized distance measure for multiple criteria decision analysis, Inf. Fusion 41 (2018) 129–150.
[25]
Liang D., Zhang Y., Xu Z., Jamaldeen A., Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry, Appl. Soft Comput. 78 (2019) 583–594.
[26]
Wu Q., Lin W., Zhou L., Chen Y., Chen H., Enhancing multiple attribute group decision making flexibility based on information fusion technique and hesitant Pythagorean fuzzy sets, Comput. Ind. Eng. 127 (2019) 954–970.
[27]
Wu Q., Zhou L., Chen Y., Chen H., An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods, Inform. Sci. 502 (2019) 394–417.
[28]
Ju Y., Wang A., Extension of VIKOR method for multi-criteria group decision making problem with linguistic information, Appl. Math. Model. 37 (5) (2013) 3112–3125.
[29]
Wu Z., Xu J., Jiang X., Zhong L., Two MAGDM models based on hesitant fuzzy linguistic term sets with possibility distributions: VIKOR and TOPSIS, Inform. Sci. 473 (2019) 101–120.
[30]
Büyüközkan G., Güler M., Smart watch evaluation with integrated hesitant fuzzy linguistic SAW-ARAS technique, Measurement 153 (2020).
[31]
Wu Z., Ahmad J., Xu J., A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information, Appl. Soft Comput. 42 (2016) 314–324.
[32]
You X.-Y., You J.-X., Liu H.-C., Zhen L., Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information, Expert Syst. Appl. 42 (4) (2015) 1906–1916.
[33]
Ghadikolaei A.S., Madhoushi M., Divsalar M., Extension of the VIKOR method for group decision making with extended hesitant fuzzy linguistic information, Neural Comput. Appl. 30 (2018) 3589–3602.
[34]
Liu J., Liang Y., Multi-granularity unbalanced linguistic group decision-making with incomplete weight information based on VIKOR method, Granul. Comput. 3 (2018) 219–228.
[35]
Ren Z., Xu Z., Wang H., Dual hesitant fuzzy VIKOR method for multi-criteria group decision making based on fuzzy measure and new comparison method, Inform. Sci. 388–389 (2017) 1–16.
[36]
Belošević I., Kosijer M., Ivić M., et al., Group decision making process for early stage evaluations of infrastructure projects using extended VIKOR method under fuzzy environment, Eur. Transp. Res. Rev. 10 (2018) 43.
[37]
Singh A., Kumar S., Picture fuzzy Choquet integral-based VIKOR for multicriteria group decision-making problems, Granul. Comput. 6 (2021) 587–601.
[38]
Liu P., Zhang K., Wang P., Wang F., A clustering- and maximum consensus-based model for social network large-scale group decision making with linguistic distribution, Inform. Sci. 602 (2022) 269–297.
[39]
Tang M., Liao H., Xu J., Streimikiene D., Zheng X., Adaptive consensus reaching process with hybrid strategies for large-scale group decision making, European J. Oper. Res. 282 (3) (2020) 957–971.
[40]
Wang F., Wan S., A comprehensive group decision-making method with interval-valued intuitionistic fuzzy preference relations, Soft Comput. 25 (1) (2021) 343–362.
[41]
Liu S., Wang B., Liu J., Group decision making under social influences based on information entropy, Granul. Comput. 5 (2020) 303–308.
[42]
Yang J., Gu D., Shanlin Y., Mei K., cao Y., MAGDM in hesitant interval-valued Pythagorean linguistic Z-number based on combined score function and entropy, Int. J. Mach. Learn. Cybern. 13 (2022) 3173–3198.
[43]
Yang W., Pang Y., T-Spherical fuzzy ORESTE method based on cross-entropy measures and its application in multiple attribute decision-making, Soft Comput. 26 (2022) 10371–10387.
[44]
Yue C., Entropy-based weights on decision makers in group decision-making setting with hybrid preference representations, Appl. Soft Comput. 60 (2017) 737–749.
[45]
Yue C., Projection-based approach to group decision-making with hybrid information representations and application to software quality evaluation, Comput. Ind. Eng. 132 (2019) 98–113.
[46]
He D., Xu J., Chen X., Information-theoretic-entropy based weight aggregation method in multiple-attribute group decision-making, Entropy 18 (6) (2016) 171.
[47]
Koksalmis E., Kabak Ö., Deriving decision makers’ weights in group decision making: An overview of objective methods, Inf. Fusion 49 (2019) 146–160.
[48]
Tian J., Guo Y., Software trustworthiness evaluation model based on a behaviour trajectory matrix, Inf. Softw. Technol. 119 (2020),.
[49]
Yang M., Gao T., Xie W., Jia L., Zhang T., The assessment of cloud service trustworthiness state based on D-S theory and Markov chain, IEEE Access 10 (2022) 68618–68632,.
[50]
Raghavan S., Chandrasekaran K., Membrane-based models for service selection in cloud, Inform. Sci. 558 (2021) 103–123,.
[51]
Wahab O.A., Cohen R., Bentahar J., Otrok H., Mourad A., Rjoub G., An endorsement-based trust bootstrapping approach for newcomer cloud services, Inform. Sci. 527 (2020) 159–175,.
[52]
Gireesha O., Kamalesh A., Krithivasan K., Shankar Sriram V., A fuzzy-multi attribute decision making approach for efficient service selection in cloud environments, Expert Syst. Appl. 206 (2022),.
[53]
Hussain A., Chun J., Cloud service scrutinization and selection framework (C3SF): A novel unified approach to cloud service selection with consensus, Inform. Sci. 586 (2022) 155–175,.
[54]
Al-Faifi A., Song B., Hassan M.M., Alamri A., Gumaei A., A hybrid multi criteria decision method for cloud service selection from smart data, Future Gener. Comput. Syst. 93 (2019) 43–57,.
[55]
Gireesha O., Somu N., Krithivasan K., V.S. S.S., IIVIFS-WASPAS: An integrated Multi-Criteria Decision-Making perspective for cloud service provider selection, Future Gener. Comput. Syst. 103 (2020) 91–110,.
[56]
Nadeem F., Evaluating and ranking cloud IaaS, PaaS and SaaS models based on functional and non-functional key performance indicators, IEEE Access 10 (2022) 63245–63257,.
[57]
Hussain A., Chun J., Khan M., A novel customer-centric methodology for optimal service selection (MOSS) in a cloud environment, Future Gener. Comput. Syst. 105 (2020) 562–580,.
[58]
Mao C., Lin R., Towey D., Wang W., Chen J., He Q., Trustworthiness prediction of cloud services based on selective neural network ensemble learning, Expert Syst. Appl. 168 (2021),.
[59]
Lim M.K., Xiong W., Wang Y., A three-tier programming model for service composition and optimal selection in cloud manufacturing, Comput. Ind. Eng. 167 (2022),.
[60]
Bawazir A., Alhalabi W., Mohamed M., Sarirete A., Alsaig A., A formal approach for matching and ranking trustworthy context-dependent services, Appl. Soft Comput. 73 (2018) 306–315,.
[61]
Ding S., Yang S.-L., Fu C., A novel evidential reasoning based method for software trustworthiness evaluation under the uncertain and unreliable environment, Expert Syst. Appl. 39 (3) (2012) 2700–2709,.
[62]
Lu L., Yuan Y., A novel TOPSIS evaluation scheme for cloud service trustworthiness combining objective and subjective aspects, J. Syst. Softw. 143 (2018) 71–86,.
[63]
Si G., Xu J., Yang J., Wen S., An evaluation model for dependability of Internet-scale software on basis of Bayesian Networks and trustworthiness, J. Syst. Softw. 89 (2014) 63–75,.
[64]
Singh S., Sidhu J., Compliance-based multi-dimensional trust evaluation system for determining trustworthiness of cloud service providers, Future Gener. Comput. Syst. 67 (2017) 109–132,.
[65]
Ma H., Zhu H., Hu Z., Li K., Tang W., Time-aware trustworthiness ranking prediction for cloud services using interval neutrosophic set and ELECTRE, Knowl.-Based Syst. 138 (2017) 27–45,.
[66]
Ju Y., Wang A., Projection method for multiple criteria group decision making with incomplete weight information in linguistic setting, Appl. Math. Model. 37 (20) (2013) 9031–9040.
[67]
Xu G., Liu F., An approach to group decision making based on interval multiplicative and fuzzy preference relations by using projection, Appl. Math. Model. 37 (6) (2013) 3929–3943.
[68]
Liao H., Zhang C., Luo L., A multiple attribute group decision making method based on two novel intuitionistic multiplicative distance measures, Inform. Sci. 467 (2018) 766–783.
[69]
Liu P., You X., Bidirectional projection measure of linguistic neutrosophic numbers and their application to multi-criteria group decision making, Comput. Ind. Eng. 128 (2019) 447–457.
[70]
Ye J., Bidirectional projection method for multiple attribute group decision making with neutrosophic numbers, Neural Comput. Appl. 28 (5) (2017) 1021–1029.
[71]
Tang G., Chiclana F., Lin X., Liu P., Interval type-2 fuzzy multi-attribute decision-making approaches for evaluating the service quality of Chinese commercial banks, Knowl.-Based Syst. 193 (2020).
[72]
Yue Z., Jia Y., A direct projection-based group decision-making methodology with crisp values and interval data, Soft Comput. 21 (9) (2017) 2395–2405.
[73]
Wan S.-P., Li S.-Q., Dong J.-Y., A three-phase method for Pythagorean fuzzy multi-attribute group decision making and application to haze management, Comput. Ind. Eng. 123 (2018) 348–363.
[74]
Yue C., Two normalized projection models and application to group decision-making, J. Intell. Fuzzy Systems 32 (6) (2017) 4389–4402.
[75]
Yue C., An interval-valued intuitionistic fuzzy projection-based approach and application to evaluating knowledge transfer effectiveness, Neural Comput. Appl. 31 (11) (2019) 7685–7706.
[76]
Yue C., A normalized projection-based group decision-making method with heterogeneous decision information and application to software development effort assessment, Appl. Intell. 49 (10) (2019) 3587–3605.
[77]
Yue C., Picture fuzzy normalized projection and extended VIKOR approach to software reliability assessment, Appl. Soft Comput. (2020).
[78]
Wei G., Picture 2-tuple linguistic Bonferroni mean operators and their application to multiple attribute decision making, Int. J. Fuzzy Syst. 19 (4) (2017) 997–1010.
[79]
Zhang X., Wang J., Hu J., On novel operational laws and aggregation operators of picture 2-tuple linguistic information for MCDM problems, Int. J. Fuzzy Syst. 20 (3) (2018) 958–969.
[80]
Peng J.J., Chen X.G., Tian C., Zhang Z.Q., Song H.Y., Dong F., Picture fuzzy large-scale group decision-making in a trust-relationship-based social network environment, Inform. Sci. 608 (2022) 1675–1701.
[81]
Yue Z., Jia Y., A group decision making model with hybrid intuitionistic fuzzy information, Comput. Ind. Eng. 87 (2015) 202–212.
[82]
Wei G., Alsaadi F.E., Hayat T., Alsaedi A., Projection models for multiple attribute decision making with picture fuzzy information, Int. J. Mach. Learn. Cybern. 9 (4) (2018) 713–719.
[83]
Yue Z., An extended TOPSIS for determining weights of decision makers with interval numbers, Knowl.-Based Syst. 24 (1) (2011) 146–153.
[84]
Yue Z., A method for group decision-making based on determining weights of decision makers using TOPSIS, Appl. Math. Model. 35 (4) (2011) 1926–1936.
[85]
Rasberry S.D., Entropy in quality systems, Accreditation Qual. Assur. 14 (2) (2009) 65–66.
[86]
McNeill F.M., Thro E., Fuzzy Logic: A Practical Approach, Academic Press, 2014.
[87]
István Á., Harmati E., Fullér R., Felde I., On stability of maximal entropy OWA operator weights, Fuzzy Sets and Systems 448 (2022) 145–156.
[88]
Thao N.X., Similarity measures of picture fuzzy sets based on entropy and their application in MCDM, Pattern Anal. Appl. 23 (2020) 1203–1213.
[89]
Arya V., Kumar S., A new picture fuzzy information measure based on Shannon entropy with applications in opinion polls using extended VIKOR-TODIM approach, Comput. Appl. Math. 39 (2020) 197.
[90]
Lu L., Yuan Y., A novel TOPSIS evaluation scheme for cloud service trustworthiness combining objective and subjective aspects, J. Syst. Softw. 143 (2018) 71–86.
[91]
Yue C., A VIKOR-based group decision-making approach to software reliability evaluation, Soft Comput. 26 (18) (2022) 9445–9464.
Recommendations
Picture fuzzy normalized projection and extended VIKOR approach to software reliability assessment
AbstractAn extended VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method in group decision-making (GDM) setting is developed in this paper. The decision information is characterized by picture fuzzy number. A new GDM model is ...
Graphical abstractDisplay Omitted
Highlights- A new normalization projection measure is developed in picture fuzzy setting.
- ...
A VIKOR-based group decision-making approach to software reliability evaluation
AbstractSoftware reliability evaluation is important to attribute of software quality. A new group decision-making is provided to evaluate software reliability, where the model is based on an extended VIsekriterijumska optimizacija i KOmpromisno Resenje ...
An integrated fuzzy multi criteria group decision making approach for ERP system selection
Decision hierarchy for software selection process has four phases, which includes goal, criteria, sub-criteria and alternatives. This paper ensures an analytical tool to define the most convenient software.Fuzzy AHP determines the weights for criteria ...
Comments
Information & Contributors
Information
Published In
Elsevier B.V.
Publisher
Elsevier Science Publishers B. V.
Netherlands
Publication History
Published: 01 February 2024
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 12 Feb 2025