Multiple State Problem Reduction and Decision Making Criteria Hybridization
DOI:
https://doi.org/10.20535/1810-0546.2016.2.61603Keywords:
Decision making problem, Multiple state problem, Reduction, Hybridization of criteriaAbstract
Background. Due to that decision making is always involving a great deal of approaches and heuristics, and poor statistics and time course can generate series of decision making problems, the problem of regarding multiple states and criteria is considered.
Objective. The goal is to develop an approach for reducing the multiple state decision making problem along with regarding multiple criteria by their hybridization to solve disambiguously a single decision making problem.
Methods. An algorithm of reducing a finite series of decision making problems to a single problem is suggested. Also a statement is formulated to hybridize decision making criteria allowing to get a single optimal alternatives’ set.
Results. Practically, this set contains just a single alternative. And, owing to the law of large numbers (of multiple criteria), the greater number of criteria is involved into the hybridization, the more reliable decision by the formulated statement is.
Conclusions. The represented multiple state problem reduction and decision making criteria hybridization both provide a researcher with the one decision making problem whose number of optimal solutions must be less than that by any other approaches. Besides, it allows to rank alternatives at higher reliability and validity. Furthermore, reliable weights (priorities) for scalarizing multicriteria problems are produced.References
G. Dede et al., “Convergence properties and practical estimation of the probability of rank reversal in pairwise comparisons for multi-criteria decision making problems”, Eur. J. Oper. Res, vol. 241, iss. 2, pp. 458–468, 2015. doi:10.1016/j.ejor. 2014.08.037
T.-Y. Chen, “Interval-valued fuzzy multiple criteria decision-making methods based on dual optimistic/pessimistic estimations in averaging operations”, Applied Soft Computing, vol. 24, pp. 923–947, 2014. doi:10.1016/j.asoc.2014.08.050
M. Alemi-Ardakani et al., “On the effect of subjective, objective and combinative weighting in multiple criteria decision making: A case study on impact optimization of composites”, Expert Systems with Applications, vol. 46, pp. 426–438, 2016. doi:10.1016/j.eswa.2015.11.003
B. Farhadinia, “Multiple criteria decision-making methods with completely unknown weights in hesitant fuzzy linguistic term setting”, Knowledge-Based Systems, vol. 93, pp. 135–144, 2016. doi:10.1016/j.knosys.2015.11.008
D. Tofan et al., “Empirical evaluation of a process to increase consensus in group architectural decision making”, Inform. Software Technol., vol. 72, pp. 31–47, 2016. doi:10.1016/j.infsof.2015.12.002
P.H. Giang and P.P. Shenoy, “Decision making on the sole basis of statistical likelihood”, Artificial Intelligence, vol. 165, iss. 2, pp. 137–163, 2005. doi:10.1016/j.artint.2005.03.004
A. Plaat et al., “Best-first fixed-depth minimax algorithms”, Artificial Intelligence, vol. 87, iss. 1-2, pp. 255–293, 1996. doi:10.1016/0004-3702(95)00126-3
B. Liu, “Minimax chance constrained programming models for fuzzy decision systems”, Inform. Sci., vol. 112, iss. 1-4, pp. 25–38, 1998. doi:10.1016/S0020-0255(98)10015-4
M. A. Howe et al., “Multi-period minimax hedging strategies”, Eur. J. Oper. Res., vol. 93, iss. 1, pp. 185–204, 1996. doi:10.1016/0377-2217(95)00167-0
S. Monghasemi et al., “A novel multi criteria decision making model for optimizing time–cost–quality trade-off problems in construction projects”, Expert Systems with Applications, vol. 42, iss. 6, pp. 3089–3104, 2015. doi:10.1016/j.eswa.2014.11.032
V.V. Romanuke, “Convergence and estimation of the process of computer implementation of the optimality principle in matrix games with apparent play horizon”, J. Automation Inform. Sci., vol. 45, iss. 10, pp. 49–56, 2013. doi:10.1615/JAutomatInfScien.v45.i10.70
H. Liao et al., “Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making”, Inform. Sci., vol. 271, pp. 125–142, 2014. doi:10.1016/j.ins.2014.02.125
Y. Ju and A. Wang, “Projection method for multiple criteria group decision making with incomplete weight information in linguistic setting”, Applied Math. Modelling, vol. 37, iss. 20-21, pp. 9031–9040, 2013. doi:10.1016/j.apm.2013.04.027
N.K. Bansal et al., “On the minimax decision rules in ranking problems”, Statistics & Probability Letters, vol. 34, iss. 2, pp. 179–186, 1997. doi:10.1016/S0167-7152(96)00180-0
M. Kadziński et al., “Multiple criteria ranking and choice with all compatible minimal cover sets of decision rules”, Knowledge-Based Systems, vol. 89, pp. 569–583, 2015. doi:10.1016/j.knosys.2015.09.004
Downloads
Published
Issue
Section
License
Copyright (c) 2017 NTUU KPI Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under CC BY 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work