87,823 research outputs found
An Extended TOPSIS Method for the Multiple Attribute Decision Making Problems Based on Interval Neutrosophic Set
The interval neutrosophic set (INS) can be easier to express the incomplete, indeterminate and inconsistent information, and TOPSIS is one of the most commonly used and effective method for multiple attribute decision making, however, in general, it can only process the attribute values with crisp numbers. In this paper, we have extended TOPSIS to INS, and with respect to the multiple attribute decision making problems in which the attribute weights are unknown and the attribute values take the form of INSs, we proposed an expanded TOPSIS method. Firstly, the definition of INS and the operational laws are given, and distance between INSs is defined. Then, the attribute weights are determined based on the Maximizing deviation method and an extended TOPSIS method is developed to rank the alternatives. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness
An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment
The aim of this paper is to develop an interactive approach for multiple attribute decision making with incomplete
weight information under linguistic environment. Some of the concepts are defined, such as the distance between
two 2-tuple linguistic variables, the expectation level of alternative, the achievement scale, the alternative
comprehensive scale under linguistic environment. Based on these concepts, we establish some linear programming
models, through which the decision maker interacts with the analyst. Furthermore, we establish a practical
interactive approach for selecting the most desirable alternative(s). The interactive process can be realized by
giving and revising the achievement scale and comprehensive scale of alternatives till the achievement scale and
the comprehensive scale are achieved to the decision makerâs request. Finally, an illustrative example is also given.The author is very grateful to the associated editor and two anonymous referees for their insightful and constructive comments and suggestions that have led to an improved version of this paper. This work was partly supported by the National Natural Science Foundation of China (No. 90924027, No. 71101043), National Basic Research Program of China (973 Program, No. 2010C B951104), Key Program of National Social Science Foundation of China (No. 10AJY005), College Philosophy and Social Science Research Project of Jiangsu Province under Grant 2011SJD630007.Xu, Y.; Wang, H.; Palacios MarquĂ©s, D. (2013). An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment. International Journal of Computational Intelligence Systems. 6(1):87-95. https://doi.org/10.1080/18756891.2013.756226S87956
Decision-making in fuzzy environment
Decision-making is a logical human judgment process for identifying and choosing alternatives based on the values and preferences of the decision maker that mostly applied in the managerial level of the concerned department of the organization/ supply chain. Recently, decision-making has gained immense popularity in industries because of their global competitiveness and to survive successfully in respective marketplace.Therefore, decision-making plays a vital role especially in purchase department for reducing material costs, minimizing production time as well as improving the quality of product or service. But, in todayâs real life problems, decision-makers generally face lot of confusions, ambiguity due to the involvement of uncertainty and subjectivity in complex evaluating criterions of alternatives. To deal such kind of vagueness in human thought the title âDecision-Making in Fuzzy Environmentâ has focused into the emerging area of research associated with decision sciences. Multiple and conflicting objectives such as âminimize costâ and âmaximize quality of serviceâ are the real stuff of the decision-makersâ daily concerns. Keeping this in mind, this thesis introduces innovative decision aid methodologies for an evaluation cum selection policy analysis, based on theory of multi criteria decision-making tools and fuzzy set theory.
In the supplier selection policy, emphasis is placed on compromise solution towards the selection of best supplier among a set of alternative candidate suppliers. The nature of supplier selection process is a complex multi-attribute group decision making (MAGDM) problem which deals with both quantitative and qualitative factors may be conflicting in nature as well as contain incomplete and uncertain information. Therefore, an application of VIKOR method combined with fuzzy logic has been reported as an efficient approach to support decision-making in supplier selection problems. This dissertation also proposes an integrated model for industrial robot selection considering both objective and subjective criteriaâs. The concept of Interval-Valued Fuzzy Numbers (IVFNs) combined with VIKOR method has been adapted in this analysis
The interval TOPSIS method for group decision making
Cel â Celem pracy jest przedstawienie nowego podejĆcia do rankingu wariantĂłw decyzyjnych z danymi przedziaĆowymi dla grupowego podejmowania decyzji, wykorzystujÄ
cego metodÄ TOPSIS.
Metodologia badania â W proponowanym podejĆciu, wszystkie pojedyncze oceny decydentĂłw sÄ
brane pod uwagÄ w wyznaczaniu koĆcowych ocen wariantĂłw decyzyjnych oraz ich rankingu. Kluczowym jego elementem jest przeksztaĆcenie macierzy decyzyjnych dostarczonych przez decydentĂłw, w macierze wariantĂłw decyzyjnych.
Wynik â Nowe podejĆcie do grupowego podejmowania decyzji wykorzystujÄ
ce metodÄ TOPSIS.
OryginalnoĆÄ/wartoĆÄ â Proponowane podejĆcie jest nowatorskie oraz Ćatwe w uĆŒyciu.Goal â 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 â 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 â A new approach for group decision making using the TOPSIS method.
Originality/value â The proposed approach is innovative and easy to use.Badania zostaĆy zrealizowane w ramach pracy nr S/WI/1/2016 i sfinansowane ze ĆrodkĂłw na naukÄ [email protected]Ć Informatyki, Politechnika BiaĆostockaAbdullah L., Adawiyah C.W.R., 2014, Simple Additive Weighting Methods of Multicriteria Decision Making and Applications: A Decade Review, âInternational Journal of Information Processing and Managementâ, 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, âExpert Systems with Applicationsâ, 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, âExpert Systems with Applicationsâ, vol. 36, pp. 11363-11368.Chen C.T., 2000, Extensions of the TOPSIS for group decision-making under fuzzy environment, âFuzzy Sets and Systemsâ, vol. 114, pp. 1-9.Cloud M. J., Kearfott R.B., Moore R.E., 2009, Introduction to Interval Analysis, SIAM, Philadelphia.Dymova L., Sevastjanova P., Tikhonenko A., 2013, A direct interval extension of TOPSIS method, âExpert Systems with Applicationsâ, vol. 40, pp. 4841-4847.Hu B.Q., Wang S., 2006, A Novel Approach in Uncertain Programming Part I: New Arithmetic and Order Relation for Interval Numbers, âJournal of Industrial and Management Optimizationâ, vol. 2(4), pp. 351-371.Hwang C.L., Yoon K. 1981 Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, Berlin.Jahanshahloo G.R., Hosseinzadeh Lotfi F., Izadikhah M., 2006, An Algorithmic Method to Extend TOPSIS for Decision Making Problems with Interval Data, âApplied Mathematics and Computationâ, vol. 175, pp. 1375-1384.Kacprzak D., 2017, Objective Weights Based on Ordered Fuzzy Numbers for Fuzzy Multiple Criteria Decision Making Methods, âEntropyâ, vol. 19(7), pp. 373.Kacprzak D., 2018, Metoda SAW z przedziaĆowymi danymi i wagami uzyskanymi za pomocÄ
przedziaĆowej entropii Shannona, âStudia Ekonomiczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicachâ, vol. 348, pp. 144-155.Kacprzak D., 2019, A doubly extended TOPSIS method for group decision making based on ordered fuzzy numbers, âExpert Systems with Applicationsâ, vol. 116, pp. 243-254.Roszkowska E., 2009, Application TOPSIS methods for ordering offers in buyer-seller transaction, âOPTIMUM, Studia Ekonomiczneâ, vol. 3(43), pp. 117-133.Roszkowska E., 2011, Multi-Criteria Decision Making Models by Applying the TOPSIS Method to Crisp and Interval Data, âMultiple Criteria Decision Makingâ, vol. 6, pp. 200-230.Roszkowska E., Kacprzak D., 2016, The fuzzy SAW and fuzzy TOPSIS procedures based on ordered fuzzy numbers, âInformation Sciencesâ, vol. 369, pp. 564-584.Rudnik K., Kacprzak D., 2017, Fuzzy TOPSIS method with ordered fuzzy numbers for flow control in a manufacturing system, âApplied Soft Computingâ, vol. 52, pp. 1020-1041.Senvar O., Otay Ä°., BoltĂŒrk E., 2016, Hospital site selection via hesitant fuzzy TOPSIS. âIFAC-PapersOnLineâ, vol. 49, pp. 1140-1145.Shih H.S., Shyur H.J., Lee E.S., 2007, An extension of TOPSIS for group decision making, âMathematical and Computer Modellingâ, vol. 45, pp. 801-813.Wang T.C., Chang T.H., 2007, Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, âExpert Systems with Applicationsâ, vol. 33, pp. 870-880.Ye F., Li Y.N., 2009, Group multi-attribute decision model to partner selection in the formation of virtual enterprise under incomplete information, âExpert Systems with Applicationsâ, vol. 36, pp. 9350-9357.Yue Z., 2011, An extended TOPSIS for determining weights of decision makers with interval numbers, âKnowledge-Based Systemsâ, vol. 24, pp. 146-153.Yue Z., 2012, Developing a straightforward approach for group decision making based on determining weights of decision makers, âApplied Mathematical Modellingâ, vol. 36, pp. 4106-4117.4(94)25627
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
Dominance Measuring Approach using Stochastic Weights
In this paper we propose an approach to obtain a ranking of alternatives in multicriteria decision-making problems when there is imprecision concerning the alternative performances, component utility functions and weights. We assume decision maker's preferences are represented by an additive multi-attribute utility function, in which weights are modeled by independent normal variables, the performance in each attribute for each alternative is an interval value and classes of utility functions are available for each attribute. The approach we propose is based on dominance measures, which are computed in a similar way that when the imprecision concerning weights is modeled by uniform distributions or by an ordinal relation. In this paper we will show how the approach can be applied when the imprecision concerning weights are represented by normal distributions. Extensions to other distributions, such as truncated normal or beta, can be feasible using Monte Carlo simulation techniques
Ranking Alternatives on the Basis of a Dominance Intensity Measure
The additive multi-attribute utility model is widely used within MultiAttribute Utility Theory (MAUT), demanding all the information describing the decision-making situation. However, these information requirements can obviously be far too strict in many practical situations. Consequently, incomplete information about input parameters has been incorporated into the decisionmaking process. We propose an approach based on a dominance intensity measure to deal with such situations. The approach is based on the dominance values between pairs of alternatives that can be computed by linear programming. These dominance values are transformed into dominance intensities from which a dominance intensity measure is derived. It is used to analyze the robustness of a ranking of technologies for the disposition of surplus weapons-grade plutonium by the Department of Energy in the USA, and compared with other dominance measuring methods
Recommended from our members
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
Intertemporal Choice of Fuzzy Soft Sets
This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade. They provide crisp or fuzzy parameterized descriptions of the universe of alternatives. On the other hand, in many decisions, costs and benefits occur at different points in time. This brings about intertemporal choices, which may involve an indefinitely large number of periods. However, the literature does not provide a model, let alone a solution, to the intertemporal problem when the alternatives are described by (fuzzy) parameterizations. In this paper, we propose a novel soft set inspired model that applies to the intertemporal framework, hence it fills an important gap in the development of fuzzy soft set theory. An algorithm allows the selection of the optimal option in intertemporal choice problems with an infinite time horizon. We illustrate its application with a numerical example involving alternative portfolios of projects that a public administration may undertake. This allows us to establish a pioneering intertemporal model of choice in the framework of extended fuzzy set theorie
An Efficient Protocol for Negotiation over Combinatorial Domains with Incomplete Information
We study the problem of agent-based negotiation in combinatorial domains. It
is difficult to reach optimal agreements in bilateral or multi-lateral
negotiations when the agents' preferences for the possible alternatives are not
common knowledge. Self-interested agents often end up negotiating inefficient
agreements in such situations. In this paper, we present a protocol for
negotiation in combinatorial domains which can lead rational agents to reach
optimal agreements under incomplete information setting. Our proposed protocol
enables the negotiating agents to identify efficient solutions using
distributed search that visits only a small subspace of the whole outcome
space. Moreover, the proposed protocol is sufficiently general that it is
applicable to most preference representation models in combinatorial domains.
We also present results of experiments that demonstrate the feasibility and
computational efficiency of our approach
- âŠ