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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 3/2022

19-04-2021 | Original Article

Sustainable competitiveness evaluation of container liners based on granular computing and social network group decision making

Authors: Xueqin Liu, Yanjun Wang, Lidong Wang

Published in: International Journal of Machine Learning and Cybernetics | Issue 3/2022

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Abstract

In the shipping industry, the sustainability of the shipping companies has received more attention besides the economic benefits. A suitable evaluation model can provide a credible sustainable improvement test and guide the operation and management of shipping companies. This study is concerned with a granular evaluation model for the sustainable competitiveness evaluation of container liners, where the interval linguistic version of the analytic hierarchy process is designed for comparing alternatives comprehensively. To obtain ideal consistent preference relations, we propose a modification method by constructing information granules and using particle swarm optimization. Moreover, based on the combination of individual preference relations and experts’ weights obtained from the social network, the aggregated overall opinion of alternatives is achieved. Furthermore, a case study evaluating the sustainable competitiveness of container liners is conducted to support the proposed evaluation framework’s feasibility and practicality.
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Appendix
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Literature
1.
Bao J, Zhou Y, Shi P et al.(2020) Sustainable competitiveness evaluation for container liners using a novel hybrid method with intuitionistic fuzzy linguistic variables. Neural Comput Adv Appl 1265:220–233CrossRef
2.
Yang C, Lu C, Haider J et al.(2013) The effect of green supply chain management on green performance and firm competitiveness in the context of container shipping in Taiwan. Transp Res Part E Logs Transp Rev 55:55–73CrossRef
3.
Yuen K, Wang X, Wong Y et al.(2017) Antecedents and outcomes of sustainable shipping practices: the integration of stakeholder and behavioural theories. Transp Res Part E Logs Transp Rev 108:18–35CrossRef
4.
Koberg E, Longoni A (2019) A systematic review of sustainable supply chain management in global supply chains. J Clean Prod 207:1084–1098CrossRef
5.
Yuen K, Li K, Xu G et al.(2019) A taxonomy of resources for sustainable shipping management: their interrelationships and effects on business performance. Transp Res Part E Logs Transp Rev 128:316–332CrossRef
6.
Saaty T (1980) The analytic hierarchy process. McGraw-Hill, New YorkMATH
7.
8.
9.
Cheng H, Chen J (1997) Automatically determine the membership function based on the maximum entropy principle. Informat Sci 96(3–4):163–182CrossRef
10.
11.
Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25(6):529–539MATH
12.
Yager R (2013) Pythagorean fuzzy subsets. In: Ifsa World Congress and Nafips Meeting 57-61
13.
Zhang S, Xu Z, He Y (2017) Operations and integrations of probabilistic hesitant fuzzy information in decision making. Inform Fus 38:1–11CrossRef
14.
Gupta M (2011) On fuzzy logic and cognitive computing: some perspectives. Sci Iran 18(3):590–592CrossRef
15.
Liu P, Liu J, Merigó J (2018) Partitioned heronian means based on linguistic intuitionistic fuzzynumbers for dealing with multi-attribute group decision making. Appl Soft Comput 62:395–422CrossRef
16.
Zadeh L (1975) The concept of a linguistic variable and its application to approximate reasoning-\({\rm I}\). Inform Sci 8(3):199–249MathSciNetMATHCrossRef
17.
Cabrerizo F, Hmouz R, Morfeq A et al.(2017) Soft consensus measures in group decision making using unbalanced fuzzy linguistic information. Soft Comput 21(11):3037–3050MATHCrossRef
18.
Jin F, Ni Z, Chen H et al.(2016) Approaches to group decision making with intuitionistic fuzzy preference relations based on multiplicative consistency. Knowl Based Syst 97:48–59CrossRef
19.
Liu P, Rong L (2020) Multiple attribute group decision-making approach based on multi-granular unbalanced hesitant fuzzy linguistic information. Int J Fuzzy Syst 22(2):604–618CrossRef
20.
Huang S (2015) Multi-criteria decision-making method based on prioritized weighted average operator with linguistic \({\rm D}\) numbers. J Jiamusi Univ (Nat Sci Ed) 33(3):464–469
21.
Liu P, Zhang X (2020) A novel approach to multi-criteria group decision-making problems based on linguistic \({\rm D}\) numbers. Comput Appl Math 39(132):2–27MathSciNet
22.
Liu H, Quan M, Li Z et al.(2019) A new integrated \({\rm MCDM}\) model for sustainable supplier selection under interval-valued intuitionistic uncertain linguistic environment. Inform Sci 486:254–270CrossRef
23.
Pedrycz W, Song M (2014) A granulation of linguistic information in \({\rm AHP}\) decision-making problems. Inform Fus 17:93–101CrossRef
24.
Tang G, Francisco C, Liu P (2020) A decision-theoretic rough set model with q-rung orthopair fuzzy information and its application in stock investment evaluation. Appl Soft Comput 91:CrossRef
25.
Song W, Zhu J (2019) A multistage risk decision making method for normal cloud model considering behavior characteristics. Appl Soft Comput 78:393–406CrossRef
26.
Lang G (2020) A general conflict analysis model based on three-way decision. Int J Mach Learn Cybern 11(5):1083–1094CrossRef
27.
Sun B, Chen X, Zhang L et al.(2020) Three-way decision making approach to conflict analysis and resolution using probabilistic rough set over two universes. Inform Sci 507:809–822MathSciNetMATHCrossRef
28.
Zhang C, Li D, Liang J (2020) Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes. Inform Sci 507:665–683MathSciNetMATHCrossRef
29.
Wang X, Li J (2020) New advances in three-way decision, granular computing and concept lattice. Int J Mach Learn Cybern 11(5):945–946CrossRef
30.
Liu F, Zhang J, Liu T (2020) A PSO-algorithm-based consensus model with the application to large-scale group decision-making. Complex Intell Syst 6:287–298CrossRef
31.
Labella L, Cohard J, Martínez J et al.(2020) An AHPSort II based analysis of the inequality reduction within European Union. Mathematics 8(4):646CrossRef
32.
Alessio I, Menelaos T, Luis M (2020) Analytic hierarchy process-fuzzy sorting: an analytic hierarchy process-based method for fuzzy classification in sorting problems. J Oper Res Soc 71(6):928–947CrossRef
33.
Ishizaka A, Pearman C, Nemery P (2012) AHPSort: an AHP-based method for sorting problems. Int J Prod Res 50(17):1–18CrossRef
34.
35.
Xu Z, Wei C (1999) A consistency improving method in the analytic hierarchy process. Eur J Oper Res 116(2):443–449MATHCrossRef
36.
Wu J, Chiclana F (2014) A social network analysis trust-consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations. Knowl Based Syst 59:97–107CrossRef
37.
Bondy J, Murty U (1977) Graph theory with applications. J Oper Res Soc 28(419):237–238
38.
Dong Y, Ding Z, Martínez L et al.(2017) Managing consensus based on leadership in opinion dynamics. Inform Sci 397:187–205MATHCrossRef
39.
Horn R, Johnson C (1994) Matrix analysis, 2nd edn. Cambridge University Press, CambridgeMATH
40.
Rosen K (2007) Discrete mathematics and its application, 6th edn. WCB/McGraw-Hill, New York
41.
Xu G, Cui Q, Shi X et al.(2019) Particle swarm optimization based on dimensional learning strategy. Swarm Evolut Comput 45:33–51CrossRef
42.
Barzilai J (1997) Deriving weights from pairwise comparison matrices. J Oper Res Soc 48(12):1226–1232MATHCrossRef
43.
Wang J, Peng J, Zhang H et al.(2015) An uncertain linguistic multi-criteria group decision-making method based on a cloud model. Group Decis Negot 24(1):171–192CrossRef
44.
45.
Cabrerizo F, Herrera V, Pedrycz W (2013) A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts. Eur J Oper Res 230(3):624–633MathSciNetMATHCrossRef
46.
Cabrerizo F, Molinera J, Pedrycz W et al.(2018) Granulating linguistic information in decision making under consensus and consistency. Expert Syst Appl 99:83–92CrossRef
47.
Callejas E, Cerrada J, Cerrada C et al.(2019) Group decision making based on a framework of granular computing for multi-criteria and linguistic contexts. IEEE Access 7:54670–54681CrossRef
48.
Liu F, Zou S, Li Q (2020) Deriving priorities from pairwise comparison matrices with a novel consistency index. Appl Math Comput 374:MathSciNetMATH
49.
Wang L, Liao B, Liu X et al.(2017) Possibility-based ELECTRE II method with uncertain linguistic fuzzy variables. Int J Patt Recogn Artif Intell 31(09):1759016CrossRef
50.
51.
52.
53.
Li C, Rodriguez R, Martinez L et al.(2018) Personalized individual semantics based on consistency in hesitant linguistic group decision making with comparative linguistic expressions. Knowl Based Syst 145:156–165CrossRef
54.
Zhang Z, Guo C (2012) A method for multi-granularity uncertain linguistic group decision making with incomplete weight information. Knowl Based Syst 26:111–119CrossRef
Metadata
Title
Sustainable competitiveness evaluation of container liners based on granular computing and social network group decision making
Authors
Xueqin Liu
Yanjun Wang
Lidong Wang
Publication date
19-04-2021
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 3/2022
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-021-01325-5

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