The interval TOPSIS method for group decision making

Cel – Celem pracy jest przedstawienie nowego podejścia do rankingu wariantów decyzyjnych z danymi przedziałowymi dla grupowego podejmowania decyzji, wykorzystującego metodę TOPSIS. Metodologia badania – W proponowanym podejściu, wszystkie pojedyncze oceny decydentów są brane pod uwagę w wyznaczaniu końcowych ocen wariantów decyzyjnych oraz ich rankingu. Kluczowym jego elementem jest przekształcenie macierzy decyzyjnych dostarczonych przez decydentów, w macierze wariantów decyzyjnych. Wynik – Nowe podejście do grupowego podejmowania decyzji wykorzystujące metodę TOPSIS. Oryginalność/wartość – Proponowane podejście jest nowatorskie oraz łatwe w użyciu.Goal – The purpose of the paper is to present a new approach to the ranking of alternatives with interval data for group decision making using the TOPSIS method. Research methodology – In the proposed approach, all individual assessments of decision makers are taken into account in determining the final assessments of alternatives and their ranking. The key stage of the proposed approach is the transformation of the decision matrices provided by the decision makers into a matrices of alternatives. Score – A new approach for group decision making using the TOPSIS method. Originality/value – The proposed approach is innovative and easy to use.Badania zostały zrealizowane w ramach pracy nr S/WI/1/2016 i sfinansowane ze środków na naukę [email protected]ł Informatyki, Politechnika BiałostockaAbdullah L., Adawiyah C.W.R., 2014, Simple Additive Weighting Methods of Multicriteria Decision Making and Applications: A Decade Review, “International Journal of Information Processing and Management”, vol. 5(1), pp. 39-49.Behzadian M., Otaghsara S.K., Yazdani M., Ignatius J., 2012, A state-of the art survey of TOPSIS applications, “Expert Systems with Applications”, vol. 39, pp. 13051-13069.Boran F.E., Genc S., Kurt M., Akay D., 2009, A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, “Expert Systems with Applications”, vol. 36, pp. 11363-11368.Chen C.T., 2000, Extensions of the TOPSIS for group decision-making under fuzzy environment, “Fuzzy Sets and Systems”, vol. 114, pp. 1-9.Cloud M. 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TOPSIS-RTCID for range target-based criteria and interval data

[EN] The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is receiving considerable attention as an essential decision analysis technique and becoming a leading method. This paper describes a new version of TOPSIS with interval data and capability to deal with all types of criteria. An improved structure of the TOPSIS is presented to deal with high uncertainty in engineering and engineering decision-making. The proposed Range Target-based Criteria and Interval Data model of TOPSIS (TOPSIS-RTCID) achieves the core contribution in decision making theories through a distinct normalization formula for cost and benefits criteria in scale of point and range target-based values. It is important to notice a very interesting property of the proposed normalization formula being opposite to the usual one. This property can explain why the rank reversal problem is limited. The applicability of the proposed TOPSIS-RTCID method is examined with several empirical litreture’s examples with comparisons, sensitivity analysis, and simulation. The authors have developed a new tool with more efficient, reliable and robust outcomes compared to that from other available tools. The complexity of an engineering design decision problem can be resolved through the development of a well-structured decision making method with multiple attributes. Various decision approches developed for engineering design have neglected elements that should have been taken into account. Through this study, engineering design problems can be resolved with greater reliability and confidence.Jahan, A.; Yazdani, M.; Edwards, K. (2021). TOPSIS-RTCID for range target-based criteria and interval data. International Journal of Production Management and Engineering. 9(1):1-14. https://doi.org/10.4995/ijpme.2021.13323OJS11491Ahn, B.S. (2017). 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Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators

[EN] There is a growing interest in environmental policies about how to implement public participation engagement in the context of water resources management. This paper presents a robust methodology, based on ordered weighted averaging (OWA) operators, to conflict resolution decision-making problems under uncertain environments due to both information and stakeholders' preferences. The methodology allows integrating heterogeneous interests of the general public and stakeholders on account of their different degree of acceptance or preference and level of influence or power regarding the measures and policies to be adopted, and also of their level of involvement (i.e., information supply, consultation and active involvement). These considerations lead to different environmental and socio-economic outcomes, and levels of stakeholders' satisfaction. The methodology establishes a prioritization relationship over the stakeholders. The individual stakeholders' preferences are aggregated through their associated weights, which depend on the satisfaction of the higher priority decision maker. The methodology ranks the optimal management strategies to maximize the stakeholders' satisfaction. It has been successfully applied to a real case study, providing greater fairness, transparency, social equity and consensus among actors. Furthermore, it provides support to environmental policies, such as the EU Water Framework Directive (WFD), improving integrated water management while covering a wide range of objectives, management alternatives and stakeholders.Llopis Albert, C.; Merigó-Lindahl, JM.; Liao, H.; Xu, Y.; Grima-Olmedo, J.; Grima-Olmedo, C. (2018). Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators. 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Decision making with Dempster-Shafer belief structure and the OWAWA operator

[EN] A new decision making model that uses the weighted average and the ordered weighted averaging (OWA) operator in the Dempster-Shafer belief structure is presented. Thus, we are able to represent the decision making problem considering objective and subjective information and the attitudinal character of the decision maker. For doing so, we use the ordered weighted averaging ¿ weighted average (OWAWA) operator. It is an aggregation operator that unifies the weighted average and the OWA in the same formulation. This approach is generalized by using quasi-arithmetic means and group decision making techniques. An application of the new approach in a group decision making problem concerning political management of a country is also developed.We would like to thank the anonymous reviewers for valuable comments that have improved the quality of the paper. Support from the Spanish Ministry of Education under project JC2009-00189 , the University of Barcelona (099311) and the European Commission (PIEFGA-2011-300062) is gratefully acknowledgedMerigó, JM.; Engemann, KJ.; Palacios Marqués, D. (2013). Decision making with Dempster-Shafer belief structure and the OWAWA operator. Technological and Economic Development of Economy. 19(sup 1):S100-S118. https://doi.org/10.3846/20294913.2013.869517SS100S11819sup 1Antuchevičienė, J., Zavadskas, E. K., & Zakarevičius, A. (2010). MULTIPLE CRITERIA CONSTRUCTION MANAGEMENT DECISIONS CONSIDERING RELATIONS BETWEEN CRITERIA / DAUGIATIKSLIAI STATYBOS VALDYMO SPRENDIMAI ATSIŽVELGIANT Į RODIKLIŲ TARPUSAVIO PRIKLAUSOMYBĘ. Technological and Economic Development of Economy, 16(1), 109-125. doi:10.3846/tede.2010.07Brauers, W. K. M., & Zavadskas, E. K. (2010). PROJECT MANAGEMENT BY MULTIMOORA AS AN INSTRUMENT FOR TRANSITION ECONOMIES / PROJEKTŲ VADYBA SU MULTIMOORA KAIP PRIEMONĖ PEREINAMOJO LAIKOTARPIO ŪKIAMS. 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A weighted aggregation operators multi-attribute group decision-making method based on interval-valued trapezoidal fuzzy numbers. Expert Systems with Applications, 38(1), 1053-1060. doi:10.1016/j.eswa.2010.07.144Merigó, J. M. (2011). A unified model between the weighted average and the induced OWA operator. Expert Systems with Applications, 38(9), 11560-11572. doi:10.1016/j.eswa.2011.03.034Merigó, J. M. (2012). The probabilistic weighted average and its application in multiperson decision making. International Journal of Intelligent Systems, 27(5), 457-476. doi:10.1002/int.21531Merigó, J. M., & Casanovas, M. (2009). Induced aggregation operators in decision making with the Dempster-Shafer belief structure. International Journal of Intelligent Systems, 24(8), 934-954. doi:10.1002/int.20368Merigó, J. M., & Casanovas, M. (2010). The uncertain induced quasi-arithmetic OWA operator. International Journal of Intelligent Systems, 26(1), 1-24. doi:10.1002/int.20444MERIGÓ, J. 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Uncertain generalized aggregation operators. Expert Systems with Applications, 39(1), 1105-1117. doi:10.1016/j.eswa.2011.07.11

Dominance Measuring Method Performance under Incomplete Information about Weights.

In multi-attribute utility theory, it is often not easy to elicit precise values for the scaling weights representing the relative importance of criteria. A very widespread approach is to gather incomplete information. A recent approach for dealing with such situations is to use information about each alternative?s intensity of dominance, known as dominance measuring methods. Different dominancemeasuring methods have been proposed, and simulation studies have been carried out to compare these methods with each other and with other approaches but only when ordinal information about weights is available. In this paper, we useMonte Carlo simulation techniques to analyse the performance of and adapt such methods to deal with weight intervals, weights fitting independent normal probability distributions orweights represented by fuzzy numbers.Moreover, dominance measuringmethod performance is also compared with a widely used methodology dealing with incomplete information on weights, the stochastic multicriteria acceptability analysis (SMAA). SMAA is based on exploring the weight space to describe the evaluations that would make each alternative the preferred one

An evaluation methodology for ergonomic design of electronic consumer products based on fuzzy axiomatic design

This article is posted with permission of OCP Science imprint. Copyright @ 2008 Old City Publishing Group.The development life cycle of software and electronic products has been shortened by the growth of rapid prototyping techniques. The evaluation of electronic consumer products should consider hardware and software as well as the ergonomic usability, emotional appeal and aesthetic integrity of the design. This research follows a systematic approach to develop an evaluation methodology for electronic mobile products on ergonomic design. The proposed methodology is based on fuzzy multi attribute decision making and fuzzy axiomatic design realized in three steps; determination of ergonomic attributes for electronic consumer products, determination of a representative set of alternatives, and selection of the best alternative in terms of ergonomic design by utilizing fuzzy axiomatic design. A case study is also provided to support the proposed methodology