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RETRACTED ARTICLE: A fuzzy multi-objective immune genetic algorithm for the strategic location planning problem

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This article was retracted on 18 January 2022

Abstract

The distribution center (DC) location problem is one of the most important decisions for logistics systems. Owing to vague concept frequently represented in decision data, some new multiple criteria based decision-making model is proposed to solve the DC location problem with significant time-effectiveness under fuzzy environment. In the proposed model, we consider time penalty cost, operation cost, damage cost, infrastructure, market conditions, government policy, technical conditions and land resources from a comprehensive view. Meanwhile, trapezoidal fuzzy numbers are used to describe the delivery time window and the service level. Then, intuitionistic fuzzy sets and immune genetic algorithm are utilized to solve the model. Finally, a numerical example is presented to illustrate the effectiveness of the proposed approach.

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References

  1. Döyen, A., Aras, N., Barbarosoğlu, G.: A two-echelon stochastic facility location model for humanitarian relief logistics. Optim. Lett. 6(6), 1123–1145 (2012)

    Article  MathSciNet  Google Scholar 

  2. Pishvaee, M.S., Farahani, R.Z., Dullaert, W.: A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Comput. Oper. Res. 37(6), 1100–1112 (2010)

    Article  Google Scholar 

  3. Alp, O., Erkut, E., Drezne, Z.: An efficient genetic algorithm for the p-median problem. Ann. Oper. Res. 122(1–4), 21–42 (2003)

    Article  MathSciNet  Google Scholar 

  4. Kengpol, A.: Design of a decision support system to evaluate logistics distribution network in Greater Mekong Subregion Countries. Int. J. Prod. Econ. 115(2), 388–399 (2008)

    Article  Google Scholar 

  5. Joshi, R., Banwet, D.K., Shankar, R.: A Delphi–AHP–TOPSIS based benchmarking framework for performance improvement of a cold chain. Expert Syst. Appl. 38(8), 10170–10182 (2011)

    Article  Google Scholar 

  6. Kahraman, C., Cebeci, U., Ulukan, Z.: Multi-criteria supplier selection using fuzzy AHP. Logistics. Inform. Manag 16(6), 382–394 (1989)

    Article  Google Scholar 

  7. Boran, F.E., Genç, S., Kurt, M., et al.: A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst. Appl. 36(8), 11363–11368 (2009)

    Article  Google Scholar 

  8. Lin, L., Yuan, X.-H., Xia, Z.-Q.: Multicriteria fuzzy decision-making method based on intuitionistic fuzzy sets. Eur. J. Oper. Res. 73(1), 84–88 (2007)

    MathSciNet  MATH  Google Scholar 

  9. Diabat, A., Kannan, D., Kaliyan, M., Svetinovic, D.: An optimization model for product returns using genetic algorithms and artificial immune system. Resour. Conserv. Recycl. 74, 156–169 (2013)

    Article  Google Scholar 

  10. Xu, X.-d.: Research on immune genetic algorithm for solving the job-shop scheduling problem. Int. J. Adv. Manuf. Technol. 34(7–8), 783–789 (2007)

    Article  Google Scholar 

  11. Garg, H.: A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems. Appl. Soft Comput. 38(6), 988–999 (2016)

    Article  Google Scholar 

  12. Zandieh, M., Fatemi Ghomi, S.M.T., Moattar Husseini, S.M.: An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times. Appl. Math. Comput. 180(1), 111–127 (2006)

    MathSciNet  MATH  Google Scholar 

  13. Awasthi, A., Chauhan, S.S.: A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning. Appl. Math. Model. 36(2), 573–584 (2012)

    Article  Google Scholar 

  14. Bouhana, A., Chabchoub, H., Abed, M., et al.: A multi-criteria decision making approach based on fuzzy theory and fuzzy preference relations for urban distribution centers’ location selection under uncertain environments. In: International Conference on Advanced Logistics and Transport, pp 556–561. IEEE (2013)

  15. Chen, C.-T.: A fuzzy approach to select the location of the distribution center. Fuzzy Sets Syst. 118(1), 65–73 (2001)

    Article  MathSciNet  Google Scholar 

  16. Cengiz, K., Ruan, D., Doǧan, I.: Fuzzy group decision-making for facility location selection. Inf. Sci. 157(1), 135–153 (2003)

    MATH  Google Scholar 

  17. Cai, X., Chen, J., Xiao, Y., Xu, X., Yu, G.: Fresh-product supply chain management with logistics outsourcing. Omega 41(4), 752–765 (2013)

    Article  Google Scholar 

  18. Xiaopeng, G., Xifei,  Y.: Low carbon distribution center’s location decision method under carbon emissions constraint condition. J. Appl. Sci. 13(11), 1988–1991 (2013)

    Article  Google Scholar 

  19. Guo, H.Y., Li, Z.L.: Structural damage identification based on Bayesian theory and improved immune genetic algorithm. Expert Syst. Appl. 39(7), 6426–6434 (2012)

    Article  Google Scholar 

  20. von der Gracht, H.A., Darkow, I.-L.: Scenarios for the logistics services industry: a Delphi-based analysis for 2025. Int. J. Prod. Econ. 127(1), 46–59 (2010)

    Article  Google Scholar 

  21. Devi, K.: Extension of VIKOR method in intuitionistic fuzzy environment for robot selection. Expert Syst. Appl. 38(11), 14163–14168 (2011)

    Google Scholar 

  22. Li, D.F.: Multiattribute decision making models and methods using intuitionistic fuzzy sets. J. Comput. Syst. Sci. 70(1), 73–85 (2005)

    Article  MathSciNet  Google Scholar 

  23. De Miguel, L., Bustince, H., Fernandez, J., et al.: Construction of admissible linear orders for interval-valued Atanassov intuitionistic fuzzy sets with an application to decision making. Inf. Fusion 27, 189–197 (2016)

    Article  Google Scholar 

  24. de Keizer, M., Akkerman, R., Grunow, M.: Logistics network design for perishable products with heterogeneous quality decay. Eur. J. Oper. Res. 262(2), 535–549 (2017)

    Article  MathSciNet  Google Scholar 

  25. Qing-dao-er-ji, R., Wang, Y.: A new hybrid genetic algorithm for job shop scheduling problem. Comput. Oper. Res. 39(10), 2291–2299 (2012)

    Article  MathSciNet  Google Scholar 

  26. Xu, Z.-s., Chen, J.: Approach to group decision making based on interval-valued intuitionistic judgment matrices. Syst. Eng. Theory Pract. 27(4), 126–133 (2007)

    Article  Google Scholar 

  27. Ye, J.: Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment. Eur. J. Oper. Res. 205(1), 202–204 (2010)

    Article  Google Scholar 

  28. Yu, Y., Xiao, T.: Pricing and cold-chain service level decisions in a fresh agri-products supply chain with logistics outsourcing. Comput. Ind. Eng. 111, 56–66 (2017)

    Article  Google Scholar 

  29. Turskis, Z., Zavadskas, E.K.: A new fuzzy additive ratio assessment method (ARAS-F). Case study: the analysis of fuzzy multiple criteria in order to select the logistic centers location. Transport 25(4), 423–432 (2010)

    Article  Google Scholar 

Download references

Acknowledgements

The first author wishes to acknowledge the financial support of the National Natural Science Foundation of China (Project No. 71471143), Center of Service Science and Engineering (Wuhan University of Science and Technology) Opening Foundation (Project No. CSSE2017KA04), and Hubei Key Laboratory for Efficient Utilization and Agglomeration of Metallurgic Mineral Resources (Wuhan University of Science and Technology) Opening Foundation (Project No. 2016zy013). Thanks for all the authors of the references who gives us inspirations and helps. The authors are grateful to the editors and anonymous reviewers for their valuables comments that improved the quality of this paper.

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Correspondence to Lei Wang.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s10586-022-03546-x

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Zhao, X., Xia, X., Wang, L. et al. RETRACTED ARTICLE: A fuzzy multi-objective immune genetic algorithm for the strategic location planning problem. Cluster Comput 22 (Suppl 2), 3621–3641 (2019). https://doi.org/10.1007/s10586-018-2212-1

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  • DOI: https://doi.org/10.1007/s10586-018-2212-1

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