Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Decision-making from multiple uncertain experts: case of distribution center location selection

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

The location selection of distribution center covers one of the important strategic decision issues for the logistics system managers. In view of the inherent uncertainty and inaccuracy of human decision-making, the future behavior of the market and companies, this paper adopts the improved multi-attribute and multi-Actor decision-making (MAADM) method as a fuzzy multi-attribute and multi-actor decision-making (FMAADM) method for solving the selection problem under an uncertain environment. The great strengths of our proposed method are: first, the integration of the decision-makers group preferences into the decision-making process, second, the consideration of the informations related to the alternatives and the criteria weights which are inaccurate, uncertain or incomplete, third, the verification of the obtained solution by both tests of concordance and non-discordance. To validate the FMAADM method, a decision support system was developed. Different experiments were provided based on comparative analysis of results and the sensitivity analysis. These experiments demonstrate the efficiency of our proposed method and its superiority over another existing methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. https://netbeans.org/.

  2. https://www.w3.org/XML/.

  3. https://poi.apache.org/.

  4. http://www.oracle.com/technetwork/java/javase/jdbc/index.html.

References

  • Agrebi M (2018) Méthodes d’aide à la décision multi-attribut et multi-acteur pour résoudre le problème de sélection dans un environnement certain/incertain: cas de la localisation des centres de distribution. Ph.D. thesis, Université de Valenciennes et du Hainaut-Cambresis

  • Agrebi M, Abed M, Omri MN (2016) A new multi-actor multi-attribute decision-making method to select the distribution centers’ location. In: IEEE symposium series on computational intelligence (SSCI). IEEE, pp 1–7

  • Agrebi M, Abed M, Omri MN (2017) ELECTRE I based relevance decision-makers feedback to the location selection of distribution centers. J Adv Transp 2017:10

    Google Scholar 

  • Alias FMA, Abdullah L, Gou X, Liao H, Herrera-Viedma E (2019) Consistent fuzzy preference relation with geometric Bonferroni mean: a fused preference method for assessing the quality of life. Appl Intell 49:1–12

    Google Scholar 

  • Arora R, Garg H (2018) A robust correlation coefficient measure of dual hesitant fuzzy soft sets and their application in decision making. Eng Appl Artif Intell 72:80–92

    Google Scholar 

  • Awasthi A, Chauhan SS, Goyal SK (2011) A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Math Comput Modell 53(1):98–109

    MathSciNet  Google Scholar 

  • Awasthi A, Adetiloye T, Crainic TG (2016) Collaboration partner selection for city logistics planning under municipal freight regulations. Appl Math Model 40(1):510–525

    MathSciNet  Google Scholar 

  • Awasthi A, Govindan K, Gold S (2018) Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. Int J Prod Econ 195:106–117

    Google Scholar 

  • Ayadi D (2010) Optimisation multicritère de la fiabilité: application du modèle de goal programming avec les fonctions de satisfactions dans l’industrie de traitement de gaz. Ph.D. thesis

  • Bashiri M, Hosseininezhad SJ (2009) A fuzzy group decision support system for multifacility location problems. Int J Adv Manuf Technol 42(5–6):533–543

    Google Scholar 

  • Bisdorff R, Dias LC, Meyer P, Mousseau V, Pirlot M (2015) Evaluation and decision models with multiple criteria. Springer, Berlin

    Google Scholar 

  • Cagri Tolga A, Tuysuz F, Kahraman C (2013) A fuzzy multi-criteria decision analysis approach for retail location selection. Int J Inf Technol Dec Mak 12(04):729–755

    Google Scholar 

  • Chan F, Kumar N, Choy K (2007) Decision-making approach for the distribution centre location problem in a supply chain network using the fuzzy-based hierarchical concept. Proc Inst Mech Eng Part B: J Eng Manuf 221(4):725–739

    Google Scholar 

  • Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114(1):1–9

    Google Scholar 

  • Chen CT (2001) A fuzzy approach to select the location of the distribution center. Fuzzy Sets Syst 118(1):65–73

    MathSciNet  Google Scholar 

  • Cheng Y, Zhou S (2016) Research of distribution center site selection based on fuzzy analytic hierarchy process. In: Proceedings of the 22nd international conference on industrial engineering and engineering management 2015. Springer, pp 335–342

  • Chen B, Qu R, Bai R, Laesanklang W (2018) A hyper-heuristic with two guidance indicators for bi-objective mixed-shift vehicle routing problem with time windows. Appl Intell 48(12):4937–4959

    Google Scholar 

  • Chou CC, Chang PC (2009) A fuzzy multiple criteria decision making model for selecting the distribution center location in China: a Taiwanese manufacturer’s perspective. Human Interface and the Management of Information. Information and Interaction, pp 140–148

  • Chu TC, Lai MT (2005) Selecting distribution centre location using an improved fuzzy MCDM approach. Int J Adv Manuf Technol 26(3):293–299

    Google Scholar 

  • Collette Y, Siarry P (2011) Optimisation multiobjective: algorithms. Editions Eyrolles, Paris

    Google Scholar 

  • Deveci M, Cali U, Kucuksari S, Erdogan N (2020) Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland. Energy 198:117317

    Google Scholar 

  • Eldemir F, Onden I (2016) Geographical information systems and multicriteria decisions integration approach for hospital location selection. Int J Inf Technol Dec Mak 15(05):975–997

    Google Scholar 

  • Ertuğrul İ (2011) Fuzzy group decision making for the selection of facility location. Group Decis Negot 20(6):725–740

    Google Scholar 

  • Fan LF, Jiang HB, Chen KS (2006) Fuzzy-analytic hierarchy process based distribution center location selection research. J Transp Syst Eng Inf Technol 1:107–110

    Google Scholar 

  • Farahani RZ, Asgari N (2007) Combination of MCDM and covering techniques in a hierarchical model for facility location: a case study. Eur J Oper Res 176(3):1839–1858

    Google Scholar 

  • Garg H, Rani D (2019) A robust correlation coefficient measure of complex intuitionistic fuzzy sets and their applications in decision-making. Appl Intell 49(2):496–512

    Google Scholar 

  • Guo-qin J, Hong-yan Y (2014) Shanghai agricultural products logistics distribution center location based on fuzzy AHP. In: International conference on logistics engineering, management and computer science, pp 861–864

  • He Y, Wang X, Lin Y, Zhou F, Zhou L (2017) Sustainable decision making for joint distribution center location choice. Transp Res Part D: Transport Environ 55:202–216

    Google Scholar 

  • Hu Y, Wu S, Cai L (2009) Fuzzy multi-criteria decision-making TOPSIS for distribution center location selection. In: International conference on networks security, wireless communications and trusted computing (NSWCTC), vol 2. IEEE, pp 707–710

  • Huschebeck M, Allen J (2005) Policy and research recommendations—I—Urban consolidation centres, last mile solutions

  • Hwang S, Thill JC (2005) Modeling localities with fuzzy sets and GIS. In: Fuzzy modeling with spatial information for geographic problems. Springer-Verlag, pp 71–104

  • Jafari A, Sharif-Yazdi M, Jafarian M (2010) A new multi-objective approach in distribution centers location problem in fuzzy environment. J Uncertain Syst 4(2):133–146

    Google Scholar 

  • Kahraman C, Gülbay M, Kabak Ö (2006) Applications of fuzzy sets in industrial engineering: a topical classification. In: Fuzzy applications in industrial engineering. Springer, pp 1–55

  • Kaya I, Çinar D (2006) Facility location selection using a fuzzy outranking method. In: Applied artificial intelligence. World Scientific, pp 359–366

  • Klose A, Drexl A (2005) Facility location models for distribution system design. Eur J Oper Res 162(1):4–29

    MathSciNet  Google Scholar 

  • Kumar A, Sah B, Singh AR, Deng Y, He X, Kumar P, Bansal R (2017) A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renew Sustain Energy Rev 69:596–609

    Google Scholar 

  • Kuo MS (2011) Optimal location selection for an international distribution center by using a new hybrid method. Expert Syst Appl 38(6):7208–7221

    Google Scholar 

  • Lee HS (2005) A fuzzy multi-criteria decision making model for the selection of the distribution center. In: Advances in natural computation, p 439

  • Lee WS (2014) A new hybrid MCDM model combining DANP with VIKOR for the selection of location—real estate brokerage services. Int J Inf Technol Dec Mak 13(01):197–224

    Google Scholar 

  • Lee HC, Chang CT (2018) Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renew Sustain Energy Rev 92:883–896

    Google Scholar 

  • Li Y, Liu X, Chen Y (2011) Selection of logistics center location using axiomatic fuzzy set and TOPSIS methodology in logistics management. Expert Syst Appl 38(6):7901–7908

    Google Scholar 

  • Li Y, Liu Y (2013) The application of fuzzy neural network in distribution center location. In: International conference on graphic and image processing (ICGIP 2012), vol 8768. International Society for Optics and Photonics, p 87680M

  • Liu S, Chan FT, Chung S (2011) A study of distribution center location based on the rough sets and interactive multi-objective fuzzy decision theory. Robot Comput-Integr Manuf 27(2):426–433

    Google Scholar 

  • Manav C, Bank HS, Lazoglu I (2013) Intelligent toolpath selection via multi-criteria optimization in complex sculptured surface milling. J Intell Manuf 24(2):349–355

    Google Scholar 

  • Melo MT, Nickel S, Saldanha-Da-Gama F (2009) Facility location and supply chain management—a review. Eur J Oper Res 196(2):401–412

    MathSciNet  Google Scholar 

  • Milosavljević M, Bursać M, Tričković G (2018) Selection of the railroad container terminal in Serbia based on multi criteria decision making methods. Dec Mak: Appl Manag Eng 1(2):1–15

    Google Scholar 

  • Munier N (2011) Methodology to select a set of urban sustainability indicators to measure the state of the city, and performance assessment. Ecol Ind 11(5):1020–1026

    Google Scholar 

  • Munier N, Hontoria E, Jiménez-Sáez F et al (2019) Strategic approach in multi-criteria decision making. International series in operations research and management science. Springer, Berlin

    Google Scholar 

  • Ou CW, Chou SY (2009) International distribution center selection from a foreign market perspective using a weighted fuzzy factor rating system. Expert Syst Appl 36(2):1773–1782

    Google Scholar 

  • Pamucar D, Deveci M, Canıtez F, Lukovac V (2020) Selecting an airport ground access mode using novel fuzzy LBWA-WASPAS-H decision making model. Eng Appl Artif Intell 93:103703

    Google Scholar 

  • Rebaa EH (2003) Génération automatique et optimisation de systèmes à inférence floue. Ph.D. thesis, Université Paris-Est Créteil Val de Marne (UPEC)

  • Roy B (1968) Classement et choix en présence de points de vue multiples. Revue française d’informatique et de recherche opérationnelle 2(8):57–75

    Google Scholar 

  • Si A, Das S, Kar S (2019) An approach to rank picture fuzzy numbers for decision making problems. Dec Mak: Appl Manag Eng 2(2):54–64

    Google Scholar 

  • Simić D, Kovačević I, Svirčević V, Simić S (2017) 50 Years of fuzzy set theory and models for supplier assessment and selection: a literature review. J Appl Logic 24:85–96

    MathSciNet  Google Scholar 

  • Sopha BM, Asih AMS, Nursitasari PD (2018) Location planning of urban distribution center under uncertainty: a case study of Yogyakarta Special Region Province, Indonesia. J Ind Eng Manag (JIEM) 11(3):542–568

    Google Scholar 

  • Takači A, Marić M, Drakulić D (2012) The role of fuzzy sets in improving maximal covering location problem (MCLP). In: 2012 IEEE 10th Jubilee international symposium on intelligent systems and informatics (SISY). IEEE, pp 103–106

  • Tayal DK, Saxena P, Sharma A, Khanna G, Gupta S (2014) New method for solving reviewer assignment problem using type-2 fuzzy sets and fuzzy functions. Appl Intell 40(1):54–73

    Google Scholar 

  • Trivedi A, Singh A (2017) A hybrid multi-objective decision model for emergency shelter location-relocation projects using fuzzy analytic hierarchy process and goal programming approach. Int J Proj Manage 35(5):827–840

    Google Scholar 

  • Turkoglu DC, Genevois ME (2017) An analytical approach for evaluation of ATM deployment problem criteria. Int J Inf Technol Dec Mak 16:1–32

    Google Scholar 

  • van Duin JR, van Kolck A, Anand N, Taniguchi E et al (2012) Towards an agent-based modelling approach for the evaluation of dynamic usage of urban distribution centres. Procedia-Soc Behav Sci 39:333–348

    Google Scholar 

  • Wang XB, Li YJ, Sun JY (2005) Research on logistics distribution center location model and fuzzy comprehensive evaluation under electronic commerce. In: Proceedings of 2005 international conference on machine learning and cybernetics, 2005, vol 5. IEEE, pp 2789–2796

  • Wang Y, Ma XL, Wang YH, Mao HJ, Zhang Y (2012) Location optimization of multiple distribution centers under fuzzy environment. J Zhejiang Univ-Sci A 13(10):782–798

    Google Scholar 

  • Wei JY, Wang C (2009) A novel approach—fuzzy ANP for distribution center location. In: International conference on machine learning and cybernetics, vol 1. IEEE, pp 537–542

  • Wolf GW (2011) Facility location: concepts, models, algorithms and case studies. In: Zanjirani Farahani R, Hekmatfar M (eds) Series: contributions to management science. Physica-Verlag, Heidelberg, p 549

    Google Scholar 

  • Xiyang S, Peng G, Zhiyuan W, Zhusheng L (2018) Fuzzy multi-target distribution center location and inventory setting model and simulation solution. In: 2018 7th international conference on industrial technology and management (ICITM). IEEE, pp 314–319

  • Xu J, Yao L, Zhao X (2011) A multi-objective chance-constrained network optimal model with random fuzzy coefficients and its application to logistics distribution center location problem. Fuzzy Optim Decis Mak 10(3):255–285

    MathSciNet  Google Scholar 

  • Yager RR (1996) On the interpretation of fuzzy if then rules. Appl Intell 6(2):141–151

    Google Scholar 

  • Yang L, Ji X, Gao Z, Li K (2007) Logistics distribution centers location problem and algorithm under fuzzy environment. J Comput Appl Math 208(2):303–315

    MathSciNet  Google Scholar 

  • Yu X, Zhang X, Mu L (2009) A fuzzy decision making model to select the location of the distribution center in logistics. In: IEEE international conference on automation and logistics (ICAL). IEEE, pp 1144–1147

  • Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—I. Inf Sci 8(3):199–249

    MathSciNet  Google Scholar 

  • Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—II. Inf Sci 8(4):301–357

    MathSciNet  Google Scholar 

  • Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—III. Inf Sci 9(1):43–80

    MathSciNet  Google Scholar 

  • Zadeh LA et al (1965) Fuzzy sets. Inf Control 8(3):338–353

    Google Scholar 

  • Zandi A, Roghanian E (2013) Extension of Fuzzy ELECTRE based on VIKOR method. Comput Ind Eng 66(2):258–263

    Google Scholar 

  • Zhang Y, Li XH, Mao HJ (2006) A methodology based on fuzzy quality function deployment and fuzzy TOPSIS for distribution center location. J Highw Transp Res Dev 9:030

    Google Scholar 

  • Zhang J, Tian C, Zhang N, Fang W (2009) Location decision model on distribution center of emergency logistics for emergency event based on multilayer fuzzy optimization. In: International conference on energy and environment technology (ICEET), vol 3. IEEE, pp 385–388

  • Zhou J, Liu B (2007) Modeling capacitated location–allocation problem with fuzzy demands. Comput Ind Eng 53(3):454–468

    Google Scholar 

  • Zhou L, Zhang G, Liu W (2015) A new method for the selection of distribution centre locations. IMA J Manag Math 28:dpv021

    MathSciNet  Google Scholar 

  • Zhuge D, Yu S, Zhen L, Wang W (2016) Multi-period distribution center location and scale decision in supply chain network. Comput Ind Eng 101:216–226

    Google Scholar 

  • Zouggari A, Benyoucef L (2012) Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem. Eng Appl Artif Intell 25(3):507–519

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maroi Agrebi.

Ethics declarations

Conflict of interest

The authors declare no potential conflict of interests

Additional information

Communicated by V. Loia.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agrebi, M., Abed, M. Decision-making from multiple uncertain experts: case of distribution center location selection. Soft Comput 25, 4525–4544 (2021). https://doi.org/10.1007/s00500-020-05461-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-020-05461-y

Keywords