Skip to main content
Erschienen in: Neural Computing and Applications 9/2019

10.02.2018 | Original Article

A new interval-valued hesitant fuzzy pairwise comparison–compromise solution methodology: an application to cross-docking location planning

verfasst von: S. Meysam Mousavi

Erschienen in: Neural Computing and Applications | Ausgabe 9/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Cross-docking location-planning problem is recognized as one of the significant issues in logistics management. To address the issue, group decision-making methods are known as useful tools to evaluate the cross-docking location candidates under conflicted criteria regarding a group of logistics decision makers’ or experts’ judgments. In this respect, the decision can be appropriately made based on incomplete information within a framework of multi-attribute group decision analysis. Interval-valued hesitant fuzzy sets (IVHFSs) theory among new extensions of fuzzy sets theory is considered to assign some interval-valued membership degrees for cross-docking location candidates in terms of the selected criteria under a set to decrease the errors. Moreover, a new hierarchical decision methodology, namely IVHF-H-PC-CS, is designed under an uncertain environment by presenting an extended interval-valued hesitant fuzzy pairwise comparison (IVHF-PC) method for computing criteria’ weights and a new interval-valued hesitant fuzzy compromise solution (IVHF-CS) approach for ranking the cross-docking location candidates. Moreover, weights of logistics decision makers are calculated and considered in the procedure of proposed IVHF-H-PC-CS methodology to decrease the judgments’ errors. In addition, a hierarchical structure in defining the criteria could help the logistics experts to assess the cross-docking location-planning problem from many aspects. Also, the experts’ judgments are aggregated in the process of proposed interval-valued hesitant fuzzy decision methodology to avoid the data loss. Finally, a real application about the cross-docking location-planning problem is provided to show the suitability and feasibility of the proposed IVHF-H-PC-CS methodology. The obtained ranking results are compared with fuzzy decision-making methods from the recent literature to confirm the computational results of this study.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96CrossRef Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96CrossRef
4.
Zurück zum Zitat Boran FE, Akay D, Yager RR (2014) A probabilistic framework for interval type-2 fuzzy linguistic summarization. IEEE Trans Fuzzy Syst 22:1640–1653CrossRef Boran FE, Akay D, Yager RR (2014) A probabilistic framework for interval type-2 fuzzy linguistic summarization. IEEE Trans Fuzzy Syst 22:1640–1653CrossRef
5.
Zurück zum Zitat Çebi F, Otay İ (2015) Multi-criteria and multi-stage facility location selection under interval type-2 fuzzy environment: a case study for a cement factory. Int J Comput Intell Syst 8:330–344CrossRef Çebi F, Otay İ (2015) Multi-criteria and multi-stage facility location selection under interval type-2 fuzzy environment: a case study for a cement factory. Int J Comput Intell Syst 8:330–344CrossRef
6.
Zurück zum Zitat Chen N, Zeshui X, Xia M (2013) Interval-valued hesitant preference relations and their applications to group decision making. Knowl Based Syst 37:528–540CrossRef Chen N, Zeshui X, Xia M (2013) Interval-valued hesitant preference relations and their applications to group decision making. Knowl Based Syst 37:528–540CrossRef
7.
Zurück zum Zitat Devi K, Yadav SP (2013) A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method. Int J Adv Manuf Technol 66:1219–1229CrossRef Devi K, Yadav SP (2013) A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method. Int J Adv Manuf Technol 66:1219–1229CrossRef
8.
Zurück zum Zitat Erdogan M (2015) An integrated multi-criteria decision-making methodology based on type-2 fuzzy sets for selection among energy alternatives in Turkey. Iran J Fuzzy Syst 12:1–25MathSciNet Erdogan M (2015) An integrated multi-criteria decision-making methodology based on type-2 fuzzy sets for selection among energy alternatives in Turkey. Iran J Fuzzy Syst 12:1–25MathSciNet
9.
Zurück zum Zitat Farhadinia B (2013) Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets. Inf Sci 240:129–144MathSciNetCrossRef Farhadinia B (2013) Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets. Inf Sci 240:129–144MathSciNetCrossRef
10.
Zurück zum Zitat Fotea VL (2008) The direct and the inverse limit of hyperstructures associated with fuzzy sets of type 2. Iran J Fuzzy Syst 5:89–94MathSciNetMATH Fotea VL (2008) The direct and the inverse limit of hyperstructures associated with fuzzy sets of type 2. Iran J Fuzzy Syst 5:89–94MathSciNetMATH
11.
Zurück zum Zitat Gitinavard H, Mousavi SM, Vahdani B (2017) Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems. Soft Comput 21(12):3247–3265CrossRef Gitinavard H, Mousavi SM, Vahdani B (2017) Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems. Soft Comput 21(12):3247–3265CrossRef
12.
Zurück zum Zitat Gitinavard H, Mousavi SM, Vahdani B (2016) A new multi-criteria weighting and ranking model for group decision-making analysis based on interval-valued hesitant fuzzy sets to selection problems. Neural Comput Appl 27:1593–1605CrossRef Gitinavard H, Mousavi SM, Vahdani B (2016) A new multi-criteria weighting and ranking model for group decision-making analysis based on interval-valued hesitant fuzzy sets to selection problems. Neural Comput Appl 27:1593–1605CrossRef
13.
Zurück zum Zitat Gitinavard H, Mousavi SM, Vahdani B, Siadat A (2016) A distance-based decision model in interval-valued hesitant fuzzy setting for industrial selection problems. Sci Iran Trans E Ind Eng 23:1928–1940 Gitinavard H, Mousavi SM, Vahdani B, Siadat A (2016) A distance-based decision model in interval-valued hesitant fuzzy setting for industrial selection problems. Sci Iran Trans E Ind Eng 23:1928–1940
14.
Zurück zum Zitat Gitinavard H, Makui A, Jabbarzadeh A (2016) Interval valued hesitant fuzzy method based on group decision analysis for estimating weights of decision makers. J Ind Syst Eng 9:96–110 Gitinavard H, Makui A, Jabbarzadeh A (2016) Interval valued hesitant fuzzy method based on group decision analysis for estimating weights of decision makers. J Ind Syst Eng 9:96–110
15.
Zurück zum Zitat Gitinavard H, Zarandi MHF (2016) A mixed expert evaluation system and dynamic interval-valued hesitant fuzzy selection approach. World Acad Sci Eng Technol Int J Math Comput Phys Electr Comput Eng 10:337–345 Gitinavard H, Zarandi MHF (2016) A mixed expert evaluation system and dynamic interval-valued hesitant fuzzy selection approach. World Acad Sci Eng Technol Int J Math Comput Phys Electr Comput Eng 10:337–345
16.
Zurück zum Zitat Gümüş M, Bookbinder JH (2004) Cross-docking and its implications in location-distribution systems. J Bus Logist 25:199–228CrossRef Gümüş M, Bookbinder JH (2004) Cross-docking and its implications in location-distribution systems. J Bus Logist 25:199–228CrossRef
17.
Zurück zum Zitat Gupta P, Mehlawat MK, Grover N (2016) Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Inf Sci 370:184–203CrossRef Gupta P, Mehlawat MK, Grover N (2016) Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Inf Sci 370:184–203CrossRef
18.
Zurück zum Zitat Hao M, Mendel JM (2014) Similarity measures for general type-2 fuzzy sets based on the α-plane representation. Inf Sci 277:197–215MathSciNetCrossRef Hao M, Mendel JM (2014) Similarity measures for general type-2 fuzzy sets based on the α-plane representation. Inf Sci 277:197–215MathSciNetCrossRef
19.
Zurück zum Zitat He Y, He Z, Shi L, Meng S (2016) Multiple attribute group decision making based on IVHFPBMs and a new ranking method for interval-valued hesitant fuzzy information. Comput Ind Eng 99:63–77CrossRef He Y, He Z, Shi L, Meng S (2016) Multiple attribute group decision making based on IVHFPBMs and a new ranking method for interval-valued hesitant fuzzy information. Comput Ind Eng 99:63–77CrossRef
20.
Zurück zum Zitat Joshi D, Kumar S (2016) Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. Eur J Oper Res 248:183–191MathSciNetCrossRef Joshi D, Kumar S (2016) Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. Eur J Oper Res 248:183–191MathSciNetCrossRef
23.
Zurück zum Zitat Li X, Wei G (2014) GRA method for multiple criteria group decision making with incomplete weight information under hesitant fuzzy setting. J Intell Fuzzy Syst 27:1095–1105MathSciNetMATH Li X, Wei G (2014) GRA method for multiple criteria group decision making with incomplete weight information under hesitant fuzzy setting. J Intell Fuzzy Syst 27:1095–1105MathSciNetMATH
24.
Zurück zum Zitat Liao H, Xu Z (2014) Some new hybrid weighted aggregation operators under hesitant fuzzy multi-criteria decision making environment. J Intell Fuzzy Syst 26:1601–1617MathSciNetMATH Liao H, Xu Z (2014) Some new hybrid weighted aggregation operators under hesitant fuzzy multi-criteria decision making environment. J Intell Fuzzy Syst 26:1601–1617MathSciNetMATH
25.
Zurück zum Zitat Makui A, Haerian L, Eftekhar M (2006) Designing a multi-objective nonlinear cross-docking location allocation model using genetic algorithm. J Ind Eng Int 2:27–42 Makui A, Haerian L, Eftekhar M (2006) Designing a multi-objective nonlinear cross-docking location allocation model using genetic algorithm. J Ind Eng Int 2:27–42
26.
Zurück zum Zitat Mendel JM (2015) On type-reduction versus direct defuzzification for type-2 fuzzy logic systems. In: Tamir D, Rishe N, Kandel A (eds) On type-reduction versus direct defuzzification for type-2 fuzzy logic systems, fifty years of fuzzy logic and its applications. Springer, Berlin, pp 387–399CrossRef Mendel JM (2015) On type-reduction versus direct defuzzification for type-2 fuzzy logic systems. In: Tamir D, Rishe N, Kandel A (eds) On type-reduction versus direct defuzzification for type-2 fuzzy logic systems, fifty years of fuzzy logic and its applications. Springer, Berlin, pp 387–399CrossRef
28.
Zurück zum Zitat Meng F, Chen X (2014) An approach to interval-valued hesitant fuzzy multi-attribute decision making with incomplete weight information based on hybrid Shapley operators. Informatica 25:617–642CrossRef Meng F, Chen X (2014) An approach to interval-valued hesitant fuzzy multi-attribute decision making with incomplete weight information based on hybrid Shapley operators. Informatica 25:617–642CrossRef
29.
Zurück zum Zitat Miyamoto S (2000) Multisets and fuzzy multisets. In: Liu ZQ, Miyamoto S (eds) Multisets and fuzzy multisets, soft computing and human-centered machines. Springer, Berlin, pp 9–33CrossRef Miyamoto S (2000) Multisets and fuzzy multisets. In: Liu ZQ, Miyamoto S (eds) Multisets and fuzzy multisets, soft computing and human-centered machines. Springer, Berlin, pp 9–33CrossRef
30.
Zurück zum Zitat Mokhtarinejad M, Ahmadi A, Karimi B, Rahmati SHA (2015) A novel learning based approach for a new integrated location-routing and scheduling problem within cross-docking considering direct shipment. Appl Soft Comput 34:274–285CrossRef Mokhtarinejad M, Ahmadi A, Karimi B, Rahmati SHA (2015) A novel learning based approach for a new integrated location-routing and scheduling problem within cross-docking considering direct shipment. Appl Soft Comput 34:274–285CrossRef
31.
Zurück zum Zitat Mousavi M, Tavakkoli-Moghaddam R (2015) Group decision making based on a new evaluation method and hesitant fuzzy setting with an application to an energy planning problem. Int J Eng Trans C Asp 28(9):1303–1311 Mousavi M, Tavakkoli-Moghaddam R (2015) Group decision making based on a new evaluation method and hesitant fuzzy setting with an application to an energy planning problem. Int J Eng Trans C Asp 28(9):1303–1311
32.
Zurück zum Zitat Mousavi SM, Tavakkoli-Moghaddam R, Jolai F (2013) A possibilistic programming approach for a location problem of multiple cross-docks and vehicle routing scheduling under uncertainty. Eng Optimi 45(10):1223–1249MathSciNetCrossRef Mousavi SM, Tavakkoli-Moghaddam R, Jolai F (2013) A possibilistic programming approach for a location problem of multiple cross-docks and vehicle routing scheduling under uncertainty. Eng Optimi 45(10):1223–1249MathSciNetCrossRef
33.
Zurück zum Zitat Mousavi SM, Vahdani B (2016) Cross-docking location selection in distribution systems: a new intuitionistic fuzzy hierarchical decision model. Int J Comput Intell Syst 9:91–109CrossRef Mousavi SM, Vahdani B (2016) Cross-docking location selection in distribution systems: a new intuitionistic fuzzy hierarchical decision model. Int J Comput Intell Syst 9:91–109CrossRef
34.
Zurück zum Zitat Nikravesh M, Zadeh LA (2004) Fuzzy partial differential equations and relational equations: reservoir characterization and modeling. Springer, BerlinCrossRef Nikravesh M, Zadeh LA (2004) Fuzzy partial differential equations and relational equations: reservoir characterization and modeling. Springer, BerlinCrossRef
35.
Zurück zum Zitat Quirós P, Alonso P, Bustince H, Díaz I, Montes S (2015) An entropy measure definition for finite interval-valued hesitant fuzzy sets. Knowl Based Syst 84:121–133CrossRef Quirós P, Alonso P, Bustince H, Díaz I, Montes S (2015) An entropy measure definition for finite interval-valued hesitant fuzzy sets. Knowl Based Syst 84:121–133CrossRef
36.
Zurück zum Zitat Rajati MR, Mendel JM (2013) Modeling linguistic probabilities and linguistic quantifiers using interval type-2 fuzzy sets. In: IEEEI FSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), pp 327–332 Rajati MR, Mendel JM (2013) Modeling linguistic probabilities and linguistic quantifiers using interval type-2 fuzzy sets. In: IEEEI FSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), pp 327–332
37.
Zurück zum Zitat Ren Z, Zeshui X, Wang H (2017) Dual hesitant fuzzy VIKOR method for multi-criteria group decision making based on fuzzy measure and new comparison method. Inf Sci 388:1–16CrossRef Ren Z, Zeshui X, Wang H (2017) Dual hesitant fuzzy VIKOR method for multi-criteria group decision making based on fuzzy measure and new comparison method. Inf Sci 388:1–16CrossRef
38.
Zurück zum Zitat Rodríguez RM, Bedregal B, Bustince H, Dong YC, Farhadinia B, Kahraman C, Martínez L, Torra V, Xu YJ, Xu ZS (2016) A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress. Inf Fusion 29:89–97CrossRef Rodríguez RM, Bedregal B, Bustince H, Dong YC, Farhadinia B, Kahraman C, Martínez L, Torra V, Xu YJ, Xu ZS (2016) A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress. Inf Fusion 29:89–97CrossRef
39.
Zurück zum Zitat Sotudian S, Fazel Zarandi MH, Turksen IB (2016) From type-I to type-II fuzzy system modeling for diagnosis of hepatitis. World Acad Sci Eng Technol Int J Comput Electr Autom Control Inf Eng 10:1280–1288 Sotudian S, Fazel Zarandi MH, Turksen IB (2016) From type-I to type-II fuzzy system modeling for diagnosis of hepatitis. World Acad Sci Eng Technol Int J Comput Electr Autom Control Inf Eng 10:1280–1288
40.
Zurück zum Zitat Stephan K, Boysen N (2011) Cross-docking. J Manag Control 22:129–137CrossRef Stephan K, Boysen N (2011) Cross-docking. J Manag Control 22:129–137CrossRef
41.
Zurück zum Zitat Tanaka H, Guo P, Zimmermann H-J (2000) Possibility distributions of fuzzy decision variables obtained from possibilistic linear programming problems. Fuzzy Sets Syst 113:323–332MathSciNetCrossRef Tanaka H, Guo P, Zimmermann H-J (2000) Possibility distributions of fuzzy decision variables obtained from possibilistic linear programming problems. Fuzzy Sets Syst 113:323–332MathSciNetCrossRef
42.
Zurück zum Zitat Temur GT, Kaya T, Kahraman C (2014) Facility location selection in reverse logistics using a type-2 fuzzy decision aid method. In: Kahraman C, Öztayşi B (eds) Supply chain management under fuzziness. Springer, Berlin, pp 591–606CrossRef Temur GT, Kaya T, Kahraman C (2014) Facility location selection in reverse logistics using a type-2 fuzzy decision aid method. In: Kahraman C, Öztayşi B (eds) Supply chain management under fuzziness. Springer, Berlin, pp 591–606CrossRef
43.
Zurück zum Zitat Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25:529–539MATH Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25:529–539MATH
44.
Zurück zum Zitat Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: IEEE international conference on fuzzy systems, pp 1378–1382 Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: IEEE international conference on fuzzy systems, pp 1378–1382
48.
Zurück zum Zitat Vahdani B, Salimi M, Mousavi SM (2015) A compromise decision-making model based on VIKOR for multi-objective large-scale nonlinear programming problems with a block angular structure under uncertainty. Sci Iran E 22(6):2571–2584 Vahdani B, Salimi M, Mousavi SM (2015) A compromise decision-making model based on VIKOR for multi-objective large-scale nonlinear programming problems with a block angular structure under uncertainty. Sci Iran E 22(6):2571–2584
49.
Zurück zum Zitat Vahdani B, Salimi M, Mousavi SM (2017) A new compromise solution model based on Dantzig–Wolf decomposition for solving belief multi-objective nonlinear programming problems with block angular structure. Int J Inf Technol Decis Mak 16(2):333–387CrossRef Vahdani B, Salimi M, Mousavi SM (2017) A new compromise solution model based on Dantzig–Wolf decomposition for solving belief multi-objective nonlinear programming problems with block angular structure. Int J Inf Technol Decis Mak 16(2):333–387CrossRef
50.
Zurück zum Zitat Wang J, Wang J, Zhang H, Chen X (2016) Multi-criteria group decision-making approach based on 2-tuple linguistic aggregation operators with multi-hesitant fuzzy linguistic information. Int J Fuzzy Syst 18(1):81–97MathSciNetCrossRef Wang J, Wang J, Zhang H, Chen X (2016) Multi-criteria group decision-making approach based on 2-tuple linguistic aggregation operators with multi-hesitant fuzzy linguistic information. Int J Fuzzy Syst 18(1):81–97MathSciNetCrossRef
51.
Zurück zum Zitat Wei G, Zhao X, Lin R (2013) Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making. Knowl Based Syst 46:43–53CrossRef Wei G, Zhao X, Lin R (2013) Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making. Knowl Based Syst 46:43–53CrossRef
52.
Zurück zum Zitat Wu D, Mendel JM (2007) Aggregation using the linguistic weighted average and interval type-2 fuzzy sets. IEEE Trans Fuzzy Syst 15:1145–1161CrossRef Wu D, Mendel JM (2007) Aggregation using the linguistic weighted average and interval type-2 fuzzy sets. IEEE Trans Fuzzy Syst 15:1145–1161CrossRef
53.
Zurück zum Zitat Xia M, Xu Z (2011) Hesitant fuzzy information aggregation in decision making. Int J Approx Reason 52:395–407MathSciNetCrossRef Xia M, Xu Z (2011) Hesitant fuzzy information aggregation in decision making. Int J Approx Reason 52:395–407MathSciNetCrossRef
54.
Zurück zum Zitat Xia M, Zeshui X, Chen N (2013) Some hesitant fuzzy aggregation operators with their application in group decision making. Group Decis Negot 22:259–279CrossRef Xia M, Zeshui X, Chen N (2013) Some hesitant fuzzy aggregation operators with their application in group decision making. Group Decis Negot 22:259–279CrossRef
55.
Zurück zum Zitat Xu Z, Yager RR (2008) Dynamic intuitionistic fuzzy multi-attribute decision making. Int J Approx Reason 48:246–262CrossRef Xu Z, Yager RR (2008) Dynamic intuitionistic fuzzy multi-attribute decision making. Int J Approx Reason 48:246–262CrossRef
56.
Zurück zum Zitat Xu Z, Yager RR (2009) Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group. Fuzzy Optim Decis Mak 8:123–139MathSciNetCrossRef Xu Z, Yager RR (2009) Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group. Fuzzy Optim Decis Mak 8:123–139MathSciNetCrossRef
57.
Zurück zum Zitat Xu Z, Yager RR (2006) Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 35:417–433MathSciNetCrossRef Xu Z, Yager RR (2006) Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 35:417–433MathSciNetCrossRef
58.
Zurück zum Zitat Xu Z, Zhang X (2013) Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowl Based Syst 52:53–64CrossRef Xu Z, Zhang X (2013) Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowl Based Syst 52:53–64CrossRef
59.
Zurück zum Zitat Yager RR (1988) On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans Syst Man Cybern 18:183–190MathSciNetCrossRef Yager RR (1988) On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans Syst Man Cybern 18:183–190MathSciNetCrossRef
60.
Zurück zum Zitat Yager RR (2016) Multicriteria decision making with ordinal/linguistic intuitionistic fuzzy sets for mobile apps. IEEE Trans Fuzzy Syst 24:590–599CrossRef Yager RR (2016) Multicriteria decision making with ordinal/linguistic intuitionistic fuzzy sets for mobile apps. IEEE Trans Fuzzy Syst 24:590–599CrossRef
62.
Zurück zum Zitat Zadeh LA, Yager R (1999) Development of fuzzy logic and soft computing methodologies. NASA Technical Report, NASA Ames Research Center Zadeh LA, Yager R (1999) Development of fuzzy logic and soft computing methodologies. NASA Technical Report, NASA Ames Research Center
63.
Zurück zum Zitat Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—I. Inf Sci 8:199–249MathSciNetCrossRef Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—I. Inf Sci 8:199–249MathSciNetCrossRef
64.
Zurück zum Zitat Zadeh LA (1994) Soft computing and fuzzy logic. IEEE Softw 11:48–56CrossRef Zadeh LA (1994) Soft computing and fuzzy logic. IEEE Softw 11:48–56CrossRef
65.
Zurück zum Zitat Zadeh LA (1997) Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 90:111–127MathSciNetCrossRef Zadeh LA (1997) Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 90:111–127MathSciNetCrossRef
66.
Zurück zum Zitat Zadeh LA (1999) A new direction in fuzzy logic-toward a computational theory of perceptions. In: Fuzzy information processing society, NAFIPS. 18th international conference of the North American, pp 1–4 Zadeh LA (1999) A new direction in fuzzy logic-toward a computational theory of perceptions. In: Fuzzy information processing society, NAFIPS. 18th international conference of the North American, pp 1–4
68.
Zurück zum Zitat Zarandi MF, Khadangi A, Karimi F, Turksen IB (2016) A computer-aided type-II fuzzy image processing for diagnosis of meniscus tear. J Digit Imaging 29:677–695CrossRef Zarandi MF, Khadangi A, Karimi F, Turksen IB (2016) A computer-aided type-II fuzzy image processing for diagnosis of meniscus tear. J Digit Imaging 29:677–695CrossRef
69.
Zurück zum Zitat Zarandi MF, Rezaee B, Turksen IB, Neshat E (2009) A type-2 fuzzy rule-based expert system model for stock price analysis. Expert Syst Appl 36:139–154CrossRef Zarandi MF, Rezaee B, Turksen IB, Neshat E (2009) A type-2 fuzzy rule-based expert system model for stock price analysis. Expert Syst Appl 36:139–154CrossRef
70.
Zurück zum Zitat Zarandi MF, Turksen IB, Torabi Kasbi O (2007) Type-2 fuzzy modeling for desulphurization of steel process. Expert Syst Appl 32:157–171CrossRef Zarandi MF, Turksen IB, Torabi Kasbi O (2007) Type-2 fuzzy modeling for desulphurization of steel process. Expert Syst Appl 32:157–171CrossRef
71.
Zurück zum Zitat Zhang Z (2013) Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making. Inf Sci 234:150–181MathSciNetCrossRef Zhang Z (2013) Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making. Inf Sci 234:150–181MathSciNetCrossRef
72.
Zurück zum Zitat Zhang Z (2017) Hesitant fuzzy multi-criteria group decision making with unknown weight information. Int J Fuzzy Syst 19(3):615–636MathSciNetCrossRef Zhang Z (2017) Hesitant fuzzy multi-criteria group decision making with unknown weight information. Int J Fuzzy Syst 19(3):615–636MathSciNetCrossRef
73.
Zurück zum Zitat Zhang Z, Wang C, Tian D, Li K (2014) Induced generalized hesitant fuzzy operators and their application to multiple attribute group decision making. Comput Ind Eng 67:116–138CrossRef Zhang Z, Wang C, Tian D, Li K (2014) Induced generalized hesitant fuzzy operators and their application to multiple attribute group decision making. Comput Ind Eng 67:116–138CrossRef
74.
Zurück zum Zitat Zimmermann H-J (1978) Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst 1:45–55MathSciNetCrossRef Zimmermann H-J (1978) Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst 1:45–55MathSciNetCrossRef
75.
76.
Zurück zum Zitat Zimmermann H-J (2011) Fuzzy set theory—and its applications. Springer, Berlin Zimmermann H-J (2011) Fuzzy set theory—and its applications. Springer, Berlin
77.
Zurück zum Zitat Zimmermann H-J (2012) Fuzzy sets, decision making, and expert systems. Springer, Berlin Zimmermann H-J (2012) Fuzzy sets, decision making, and expert systems. Springer, Berlin
Metadaten
Titel
A new interval-valued hesitant fuzzy pairwise comparison–compromise solution methodology: an application to cross-docking location planning
verfasst von
S. Meysam Mousavi
Publikationsdatum
10.02.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 9/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3355-y

Weitere Artikel der Ausgabe 9/2019

Neural Computing and Applications 9/2019 Zur Ausgabe

S.I. : Emergence in Human-like Intelligence towards Cyber-Physical Systems

Open-circuit fault detection for three-phase inverter based on backpropagation neural network

S.I. : Emergence in Human-like Intelligence towards Cyber-Physical Systems

Forest fire forecasting using ensemble learning approaches

S.I. : Emergence in Human-like Intelligence towards Cyber-Physical Systems

Research on partial fingerprint recognition algorithm based on deep learning