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An approach to the production plant location selection based on the use of the Atanassov interval-valued intuitionistic fuzzy sets

Abstract

Location planning is one of very important tasks in the manufacturing industry. There are various factors that influence the selection of a location of a production plant. In cases of selection, when uncertainty and a need for predicting are significantly manifested, the use of fuzzy or grey numbers can be very useful. That is why an approach based on the use of Interval-Valued Intuitionistic Fuzzy Numbers (IVIFNs) for the selection of the most appropriate location of a production plant is considered in this article. The efficiency of the proposed approach is considered on an example, based on the real problem of the smelter and refinery production plant selection.


First Published Online: 7 May 2017

Keyword : facility location selection, production allocation problem, intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy numbers, score function

How to Cite
Stanujkić, D., & Meidutė-Kavaliauskienė, I. (2017). An approach to the production plant location selection based on the use of the Atanassov interval-valued intuitionistic fuzzy sets. Transport, 33(3), 835-842. https://doi.org/10.3846/16484142.2017.1321041
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May 17, 2017
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References

Atanassov, K. T. 1994. New operations defined over the intuitionistic fuzzy sets, Fuzzy Sets and Systems 61(2): 137–142. https://doi.org/10.1016/0165-0114(94)90229-1

Atanassov, K.; Gargov, G. 1989. Interval valued intuitionistic fuzzy sets, Fuzzy Sets and Systems 31(3): 343–349. https://doi.org/10.1016/0165-0114(89)90205-4

Atanassov, K. T. 1986. Intuitionistic fuzzy sets, Fuzzy Sets and Systems 20(1): 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

Atanassov, K.; Pasi, G.; Yager, R. 2002. Intuitionistic fuzzy interpretations of multi-person multi-criteria decision making, in 2002 First International IEEE Symposium Intelligent Systems, 2002: Proceedings, 10–12 September 2002, Varna, Bulgaria. https://doi.org/10.1109/IS.2002.1044238

Badri, M. A. 1999. Combining the analytic hierarchy process and goal programming for global facility location-alloca-tion problem, International Journal of Production Economics 62(3): 237–248. https://doi.org/10.1016/S0925-5273(98)00249-7

Barda, O. H.; Dupuis, J.; Lencioni, P. 1990. Multicriteria loca-tion of thermal power plants, European Journal of Operational Research 45(2–3): 332–346. https://doi.org/10.1016/0377-2217(90)90197-J

Bellman, R. E.; Zadeh, L. A. 1970. Decision-making in a fuzzy environment, Management Science 17(4): B141–B146. https://dx.doi.org/10.1287/mnsc.17.4.B141

Chandra, P.; Fisher, M. L. 1994. Coordination of production and distribution planning, European Journal of Operational Research 72(3): 503–517. https://doi.org/10.1016/0377-2217(94)90419-7

Chen, S.-M.; Tan, J.-M. 1994. Handling multicriteria fuzzy de-cision-making problems based on vague set theory, Fuzzy sets and systems 67(2): 163–172. https://doi.org/10.1016/0165-0114(94)90084-1

Chou, C.-C. 2007. A fuzzy MCDM method for solving marine transshipment container port selection problems, Applied Mathematics and Computation 186(1): 435–444. https://doi.org/10.1016/j.amc.2006.07.125

Chou, S.-Y.; Chang, Y.-H.; Shen, C.-Y. 2008. A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective at-tributes, European Journal of Operational Research 189(1): 132–145. https://doi.org/10.1016/j.ejor.2007.05.006

De, S. K.; Biswas, R.; Roy, A. R. 2000. Some operations on intuitionistic fuzzy sets, Fuzzy Sets and Systems 114(3): 477–484. https://doi.org/10.1016/S0165-0114(98)00191-2

Dymova, L.; Sevastjanov, P. 2011. Operations on intuitionistic fuzzy values in multiple criteria decision making, Scientific Research of the Institute of Mathematics and Computer Science 10(1): 41–48.

Hong, D. H.; Choi, C.-H. 2000. Multicriteria fuzzy decision-making problems based on vague set theory, Fuzzy Sets and Systems 114(1): 103–113. https://doi.org/10.1016/S0165-0114(98)00271-1

Hwang, C.-L.; Lin, M. J. 1987. Group Decision Making under Multiple Criteria: Methods and Applications. Springer. 400 p.

Hwang, C.-L.; Yoon, K. 1981. Multiple Attribute Decision Making: Methods and Applications: a State-of-the-Art Survey. 1st edition, Springer. 269 p.

Jayaraman, V.; Pirkul, H. 2001. Planning and coordination of production and distribution facilities for multiple com-modities, European Journal of Operational Research 133(2): 394–408. https://doi.org/10.1016/S0377-2217(00)00033-3

Keršulienė, V.; Zavadskas, E. K.; Turskis, Z. 2010. Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA), Journal of Business Economics and Management 11(2): 243–258. https://dx.doi.org/10.3846/jbem.2010.12

Li, D.-F. 2005. Multiattribute decision making models and methods using intuitionistic fuzzy sets, Journal of Computer and System Sciences 70(1): 73–85. https://doi.org/10.1016/j.jcss.2004.06.002

Liang, G.-S.; Wang, M.-J. J. 1991. A fuzzy multi-criteria decision-making method for facility site selection, International Journal of Production Research 29(11): 2313–2330. https://doi.org/10.1080/0020754910894808

Liu, S.; Papageorgiou, L. G. 2013. Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry, Omega: The Inter-national Journal of Management Science 41(2): 369–382. https://doi.org/10.1016/j.omega.2012.03.007

Mairs, T. G.; Wakefield, G. W.; Johnson, E. L.; Spielberg, K. 1978. On a production allocation and distribution prob-lem, Management Science 24(15): 1622–1630. https://doi.org/10.1287/mnsc.24.15.1622

Maric, M.; Stanimirovic, Z.; Djenic, A.; Stanojevic, P. 2014. Memetic algorithm for solving the multilevel uncapacitated facility location problem, Informatica 25(3): 439–466. https://doi.org/10.15388/Informatica.2014.23

Mousavi, S. M.; Tavakkoli-Moghaddam, R.; Heydar, M.; Ebrahimnejad, S. 2013. Multi-criteria decision making for plant location selection: an integrated Delphi–AHP–PRO-METHEE methodology, Arabian Journal for Science and Engineering 38(5): 1255–1268. https://doi.org/10.1007/s13369-012-0361-8

Ray, A.; De, A.; Dan, P. K. 2015. Facility location selection using complete and partial ranking MCDM methods, International Journal of Industrial and Systems Engineering19(2): 262–276. https://doi.org/10.1504/IJISE.2015.067251

Saaty, T. L. 1977. A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15(3): 234–281. https://doi.org/10.1016/0022-2496(77)90033-5

Shen, F.; Xu, J.; Xu, Z. 2015. An automatic ranking approach for multi-criteria group decision making under intuitionistic fuzzy environment, Fuzzy Optimization and Decision Making 14(3): 311–334. https://doi.org/10.1007/s10700-014-9201-5

Szmidt, E.; Kacprzyk, J. 2002. Using intuitionistic fuzzy sets in group decision making, Control and Cybernetics 31(4): 1037–1053.

Szmidt, E.; Kacprzyk, J. 2000. Distances between intuitionistic fuzzy sets, Fuzzy Sets and Systems 114(3): 505–518. https://doi.org/10.1016/S0165-0114(98)00244-9

Szmidt, E.; Kacprzyk, J. 1996. Remarks on some applications of intuitionistic fuzzy sets in decision making, Notes on Intuitionistic Fuzzy Sets 2(3): 22–31.

Wang, X. 2008. Fuzzy number intuitionistic fuzzy arithmetic aggregation operators, International Journal of Fuzzy Systems 10(2): 104–111.

Wei, G.-W. 2011. Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making, Expert Systems with Applications 38(9): 11671–11677. https://doi.org/10.1016/j.eswa.2011.03.048

Wei, G.; Zhao, X. 2012. Some induced correlated aggregating operators with intuitionistic fuzzy information and their application to multiple attribute group decision making, Expert Systems with Applications 39(2): 2026–2034. https://doi.org/10.1016/j.eswa.2011.08.031

Wei, G.; Zhao, X.; Lin, R. 2010. Some induced aggregating operators with fuzzy number intuitionistic fuzzy information and their applications to group decision making, International Journal of Computational Intelligence Systems 3(1): 84–95. https://dx.doi.org/10.1080/18756891.2010.9727679

Xu, Z. 2011. Approaches to multiple attribute group decision making based on intuitionistic fuzzy power aggregation operators, Knowledge-Based Systems 24(6): 749–760. https://doi.org/10.1016/j.knosys.2011.01.011

Xu, Z.-S. 2007. Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making, Control and Decision 22(2): 215–219. (in Chinese).

Xu, Z.-S.; Chen, J. 2007. Approach to group decision making based on interval-valued intuitionistic judgment matrices, Systems Engineering – Theory & Practice 27(4): 126–133. https://doi.org/10.1016/S1874-8651(08)60026-5

Xu, Z.; Liao, H. 2015. A survey of approaches to decision making with intuitionistic fuzzy preference relations, Knowledge-Based Systems 80: 131–142. https://doi.org/10.1016/j.knosys.2014.12.034

Xu, Z.; Yager, R. R. 2006. Some geometric aggregation opera-tors based on intuitionistic fuzzy sets, International Journal of General Systems 35(4): 417–433. https://doi.org/10.1080/03081070600574353

Zadeh, L. A. 1965. Fuzzy sets, Information and Control 8(3): 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X