Multicriteria choice based on criteria importance methods with uncertain preference information

Nelyubin, A. P.; Podinovski, V. V.

doi:10.1134/s0965542517090093

Cited by 9 publications

(9 citation statements)

References 12 publications

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“…Nelyubin and Podinovski () proposed a MCDM/MCDA choice method to model partial criteria weight information assigning a uniform probability distribution to the criteria weights and applying Monte Carlo simulation. Therefore, this method is a volume‐based method for decision making under partial information, such as the stochastic multi‐criteria acceptability analysis (SMAA) family of methods, presented as follow.…”

Section: Resultsmentioning

confidence: 99%

Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

Pelissari

Oliveira

Abackerli³

et al. 2018

Int Trans Operational Res

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There are a few studies in the literature regarding possible types of uncertainty in input data of multi-criteria decision making (MCDM) or multi-criteria decision analysis (MCDA) problems and the techniques employed to deal with each of them. Therefore, the aim of this study is to identify the different types of uncertainty that occur in input data of MCDM/MCDA problems and the most appropriate techniques to deal with each one of these uncertainty types. In this paper, a comprehensive literature review is presented in order to meet this objective. We selected and summarized 134 international journal articles. They were analyzed based on the type of data with uncertainty, the type of uncertainty, and the technique used to model it. We identified three distinct types of uncertainty in input data of MCDM/MCDA problems, namely (i) uncertainty due to ambiguity, (ii) uncertainty due to randomness, and (iii) uncertainty due to partial information. We identified a new generation of fuzzy approaches including Type-2, intuitionistic, and hesitant fuzzy sets (FSs), which are used to model these types of uncertainty alongside other approaches such as traditional FSs theory, probability theory, evidential reasoning theory, rough set theory, and grey numbers. Finally, a framework that indicates techniques used in different decision-making contexts under uncertainty is proposed.

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Section: Resultsmentioning

confidence: 99%

Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

Pelissari

Oliveira

Abackerli³

et al. 2018

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…Employing the CIT methods, it is possible to obtain a quantitative assessment of the value function of each alternative, specifying quantitative information about the importance of criteria and their scale [11]. However, this is a more laborious process, therefore, in this article, to estimate the value function, we use the approach proposed in [12].…”

Section: Theory Of Criteria Importancementioning

confidence: 99%

“…Step 4. In [12] the DM's preferences are represented in the form of numerical parameters 1 ( ,..., )…”

Section: Theory Of Criteria Importancementioning

confidence: 99%

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Thermal Performance Assessment of Wall Assemblies: Criteria Importance Theory and Ahp Approach

Biks

Ratushnyak

Lyalyuk

et al. 2022

CEJ

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The problem of the “best” choice in terms of the ecological, durable, cheap and energy-effective material of envelope construction has been considered in the paper. For the numerical assessment of the thermal performance, the MCDA techniques as Analytical Hierarchy Process (AHP) and Criteria Importance Theory (CIT) were used. There were proposed eight types of wall assemblies from a natural material, namely: Hempcrete, Adobe, Strawbale panel, Earthbag, Cordwood, SIP (plywood+ecofiber), Hempcrete+straw and Compositional building thermo-block. As a objective function for the search of the best alternative the integral index was proposed which consist of thermo-physical and economic criteria. As the thermo-physical criteria component of the index were taken the u-value of the envelope W/m2K, the dimensionless decrement factor of the envelope f and the internal areal heat capacity of the envelope k1, kJ/m2K according to ISO 13786:2017. As economic criteria of the integral index, the authors proposed the cost of the wall material Q, UAH/m2 and the mass of the wall m, kg/m2. The analysis of the conducted research has shown, that from the one hand there is no absolute “leader” in the ranking of the wall assemblies according to the proposed criteria and MCDA technique, but from the other hand by comparison of the results, there were revealed that the top three alternatives in both AHP and CIT technique are walls of “B”, “D” and “E” type with different point order, achieved in each MCDA calculation technique.

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“…Multi-objective train operation optimization has been a hot issue in the field of railway research in recent years. To obtain more satisfactory optimization results, a multi-objective optimization model preference scale changes with the change of multi-criteria decision-making problem is proposed, and Monte Carlo method is used to verify the feasibility of the algorithm [24].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Shark Smell Optimization Algorithm Using Incorporated Composite Angle Cosine for Automatic Train Operation

Wang

Sheng

et al. 2020

Energies

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In this paper, an improved multi-objective shark smell optimization algorithm using composite angle cosine is proposed for automatic train operation (ATO). Specifically, when solving the problem that the automatic train operation velocity trajectory optimization easily falls into local optimum, the shark smell optimization algorithm with strong searching ability is adopted, and composite angle cosine is incorporated. In addition, the dual-population evolution mechanism is adopted to restrain the aggregation phenomenon in shark population at the end of the iteration to suppress the local convergence. Correspondingly, the composite angle cosine, considering the numerical difference and preference difference, is used as the evaluation index, which ameliorates the shortcoming that the traditional evaluation index is not objective and reasonable. Finally, the Matlab/simulation and hardware-in-the-loop simulation (HILS) results for automatic train operation show that the improved optimization algorithm proposed in this paper has better optimization performance.

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Multicriteria choice based on criteria importance methods with uncertain preference information

Cited by 9 publications

References 12 publications

Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

Thermal Performance Assessment of Wall Assemblies: Criteria Importance Theory and Ahp Approach

Multi-Objective Shark Smell Optimization Algorithm Using Incorporated Composite Angle Cosine for Automatic Train Operation

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