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OborHealth & Medicine716 Psychology570 Business & Finance410 Engineering330 Life Sciences263 Education261 Research Practice

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Natural Sciences236

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MetodaStatistika1,836 Umělá inteligence a strojové učení1,661 Vědy o rozhodování932 Výzkumné metody1,354 Měření1,745 Kauzalita a důkazy532 Výzkumná praxe118

852 metod · Vědy o rozhodováníVymazat

Skutečné metody odpovídající vašemu filtru.

SeřaditPopularita A–Z Z–A Nejnovější

clinical psychology

Quick Inventory of Depressive Symptomatology

The Quick Inventory of Depressive Symptomatology is a 16-item assessment designed by A. John Rush and colleagues to efficiently measure the severity of depressive symptoms in adults. Published in Biological Psychiatry in 2003, the QIDS exists in both self-report (QIDS-SR) and clinician-rated (QIDS-C) versions. It was d

decision making

RAFSI

RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval) is a ranking multi-criteria decision-making (MCDM) method introduced by Žižović, M., Pamučar, D., Albijanić, M., Chatterjee, P., Pribićević, I. in 2020. It turns a decision matrix of alternatives scored on multi

decision making

RAM

RAM (Root Assessment Method) is a ranking multi-criteria decision-making (MCDM) method introduced by Sotoudeh-Anvari, A. in 2023. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Random Utility Model

The Random Utility Model explains discrete choice behavior by assuming agents derive uncertain utilities from alternatives and choose the option yielding highest utility. Introduced by Daniel McFadden in 1974, the model decomposes utility into systematic (observable) and random (idiosyncratic) components, permitting pr

decision making

Rank Aggregation

Rank Aggregation is a family of methods that combine multiple ranked lists of alternatives into a single consensus ranking. Formally studied in the context of web search by Dwork, Kumar, Naor, and Sivakumar (2001), these methods address the problem of synthesizing divergent preference orderings from multiple sources —

decision making

RANK-REVERSAL

RANK-REVERSAL (Rank Reversal Analysis — Detection of ranking instability when alternatives are added/removed) is a ranking multi-criteria decision-making (MCDM) method introduced by Triantaphyllou, E. in 2000. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

RAPS

RAPS (Ranking of Alternatives based on Preference Strength) is a ranking multi-criteria decision-making (MCDM) method introduced by Dezert, J., Tchamova, A. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

RAT

RAT (Reference Alternative based Aggregation Technique) is a aggregationoperator multi-criteria decision-making (MCDM) method introduced by Orakçı, E. in 2024. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

RAWEC

RAWEC (Ranking Alternatives With Equal Criteria weights) is a ranking multi-criteria decision-making (MCDM) method introduced by Puška, A., Štilić, A., Pamučar, D., Božanić, D., Nedeljković, M. in 2024. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

psychology of religion

RCI-10

The Religious Commitment Inventory-10 (RCI-10), developed by Worthington and colleagues in 2003, is a brief 10-item self-report measure of religious commitment: the degree to which an individual dedicates themselves to religious beliefs, practices, and community. The RCI-10 distinguishes between two dimensions of commi

decision making

REGIME

REGIME (Ordinal multi-criteria method based on pairwise regime analysis) is a ranking multi-criteria decision-making (MCDM) method introduced by Hinloopen, E., Nijkamp, P., Rietveld, P. in 1983. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

operations management

Reliability Block Diagram

A Reliability Block Diagram (RBD) is a visual representation of a system's architecture that models how component reliabilities combine to determine overall system reliability. Each block represents a component or subsystem with a known reliability (probability of functioning without failure), and connections between b

decision making

REVISED-SIMOS

REVISED-SIMOS (Revised Simos Procedure — deck-of-cards rank-based weight elicitation (Figueira & Roy 2002)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Figueira, J., Roy, B. in 2002. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproduci

problem structuring

Rich Picture

A Rich Picture is a free-form, annotated drawing used in the early exploratory stage of Soft Systems Methodology to represent the full complexity of a problematic situation. Developed by Peter Checkland at Lancaster University, it captures people, roles, concerns, processes, conflicts, and environmental factors in a si

decision making

RIM

RIM (Reference Ideal Method) is a ranking multi-criteria decision-making (MCDM) method introduced by Cables, E., Lamata, M. T., Verdegay, J. L. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

experimental design

Risk-based Six Sigma DMAIC

Risk-based Six Sigma DMAIC embeds structured risk assessment — typically failure mode and effects analysis (FMEA), risk priority numbers (RPN), or probabilistic risk tools — at each stage of the standard DMAIC cycle. The goal is not only to reduce defects and variation but to prioritize improvement actions by their ris

Robust Ant Colony Optimization

Robust Ant Colony Optimization (Robust ACO) extends the classic ant colony metaheuristic by explicitly incorporating parameter uncertainty and worst-case or expected-case robustness criteria into the solution search. Rather than optimizing for a single nominal scenario, it seeks solutions that perform well across a ran

Robust Genetic Algorithm

The Robust Genetic Algorithm (RGA) extends standard genetic algorithms to find solutions that perform well not only at the nominal design point but also when subjected to uncertainty in decision variables, parameters, or fitness evaluations. By incorporating explicit robustness measures into selection pressure, RGA bal

Robust goal programming

Robust Goal Programming (RGP) extends classical goal programming to handle uncertain or ambiguous model parameters. Instead of minimizing deviations from crisp targets, it seeks solutions that remain feasible and near-optimal across a range of plausible scenarios or uncertain data realizations. RGP is particularly valu

Robust Integer Programming

Robust Integer Programming (RIP) finds integer or binary solutions that remain feasible and near-optimal across all scenarios in a prescribed uncertainty set. Rather than assuming exact knowledge of data, RIP hedges against the worst-case realization of uncertain costs or constraint coefficients, delivering decisions t

Robust Linear Programming

Robust Linear Programming (RLP) extends classical linear programming to handle uncertainty in problem data — cost coefficients, constraint coefficients, or right-hand sides — by requiring solutions to remain feasible and near-optimal across all realizations of uncertain parameters within a defined uncertainty set. It r

Robust Mixed-Integer Programming

Robust Mixed-Integer Programming (RMIP) combines mixed-integer programming with robust optimization to find solutions that remain feasible and near-optimal despite uncertain parameters. Instead of assuming fixed data, it protects decisions against adversarial or worst-case realizations of uncertain inputs, using an exp

Robust NSGA-II

Robust NSGA-II extends the classic NSGA-II evolutionary algorithm to account for parametric uncertainty, finding Pareto-optimal trade-off solutions that remain high-performing even when input parameters deviate from their nominal values. Instead of optimizing objective values at a single point, it evaluates each candid

Robust Optimization

Robust optimization is a mathematical programming framework, formalised by Ben-Tal and Nemirovski in the late 1990s and made broadly tractable by Bertsimas and Sim (2004), that finds decisions guaranteed to perform acceptably under every scenario within a predefined uncertainty set — rather than assuming parameter valu

Robust Particle Swarm Optimization

Robust Particle Swarm Optimization (Robust PSO) extends the classical PSO metaheuristic to explicitly account for uncertainty in the objective function, constraints, or decision variables. Rather than optimizing a single nominal objective, each candidate solution is evaluated over a set of uncertainty scenarios, and fi

Robust Queueing Simulation

Robust Queueing Simulation integrates robustness analysis into queueing system simulation by considering worst-case or uncertainty-set-driven scenarios for arrival rates, service distributions, and queue disciplines. It produces performance guarantees that hold across an entire family of plausible input distributions,

Robust Simulated Annealing

Robust Simulated Annealing (RSA) adapts the classical simulated annealing metaheuristic to seek solutions that perform well not just under nominal conditions but across the full range of uncertain or adversarial parameter values. By embedding a robustness evaluation — worst-case, expected-case, or regret-based — into t

experimental design

Robust Six Sigma DMAIC

Robust Six Sigma DMAIC embeds Taguchi's robust design philosophy within the classic Define-Measure-Analyze-Improve-Control framework. Rather than optimizing a process only for average performance, this hybrid approach simultaneously minimizes process variation caused by noise factors — environmental shifts, material lo

Robust Tabu Search

Robust Tabu Search (RTS) extends the classical Tabu Search metaheuristic by evaluating candidate solutions not only on their nominal objective value but also on their performance under uncertainty. Instead of seeking the best solution for a single scenario, RTS seeks solutions that perform well across a range of scenar

decision making

ROC-WEIGHT

ROC-WEIGHT (ROC — Rank Order Centroid weights (rank-based surrogate weights)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Barron, F. H., Barrett, B. E. in 1996. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

quality management

Root Cause Analysis

Root Cause Analysis (RCA) is a structured, systematic method for identifying the fundamental causes of defects, failures, or undesirable outcomes rather than treating surface-level symptoms. Popularised by Japanese quality engineer Kaoru Ishikawa in the 1960s–1980s, and formally codified in his 1986 Guide to Quality Co

decision making

ROUGH-ARAS

ROUGH-ARAS (Rough-ARAS — Rough extension of ARAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Daoud Ben Amor, W., Moalla Frikha, H., Martínez López, L. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-COPRAS

ROUGH-COPRAS (Rough-COPRAS — Rough extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D. Božanić, D. Lukovac, V. Komazec, N. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-DRSA

ROUGH-DRSA (Rough-DRSA — Rough extension of DRSA) is a ranking multi-criteria decision-making (MCDM) method introduced by Greco, S., Matarazzo, B., Słowiński, R. in 2001. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-EDAS

ROUGH-EDAS (Rough-EDAS — Rough extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Paul, V.K. Chakraborty, S. Chakraborty, S. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-MABAC

ROUGH-MABAC (Rough-MABAC — Rough extension of MABAC) is a ranking multi-criteria decision-making (MCDM) method introduced by Jia, F., Liu, Y., Wang, X. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-MARCOS

ROUGH-MARCOS (Rough-MARCOS — Rough extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Matić, B. Marinković, M. Jovanović, S. Sremac, S. Stević, Ž. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-MOORA

ROUGH-MOORA (Rough-MOORA — Rough extension of MOORA) is a ranking multi-criteria decision-making (MCDM) method introduced by Brauers, W.K.M. Zavadskas, E.K. in 2006. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-SAW

ROUGH-SAW (Rough-SAW — Rough extension of SAW) is a ranking multi-criteria decision-making (MCDM) method introduced by Stević, Ž. Pamučar, D. Zavadskas, E.K. Ćirović, G. Prentkovskis, O. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-TODIM

ROUGH-TODIM (Rough-TODIM — Rough extension of TODIM) is a ranking multi-criteria decision-making (MCDM) method introduced by Tiwari, V. Khanna, P. Tandon, P. in 2024. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-TOPSIS

ROUGH-TOPSIS (Rough-TOPSIS — Rough extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Song, W. Ming, X. Wu, Z. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-VIKOR

ROUGH-VIKOR (Rough-VIKOR — Rough extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Zhu, G. Hu, J. Qi, J. Gu, C. Peng, Y. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROUGH-WASPAS

ROUGH-WASPAS (Rough-WASPAS — Rough extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Stojić, G. Stević, Ž. Antuchevičienė, J. Pamučar, D. Vasiljević, M. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

ROV

ROV (Range of Value method) is a ranking multi-criteria decision-making (MCDM) method introduced by Yakowitz, D. S., Lane, L. J., Szidarovszky, F. in 1993. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Runge Kutta Optimizer

The Runge Kutta Optimizer (RKO) is a metaheuristic algorithm introduced by Khatri et al. in 2023 that leverages numerical integration principles from the Runge-Kutta method. Instead of biological inspiration, RKO grounds optimization in mathematical principles of differential equations and numerical integration. The al

operations research

Safety Stock

Safety stock is an additional quantity of inventory held beyond expected demand during a replenishment lead time, designed to protect against stockouts caused by demand or supply uncertainty. Reorder-point models formalize this buffer by setting a trigger inventory level at which a new order is placed. Systematically d

decision making

SAPEVO-M

SAPEVO-M (Simple Aggregation of Preferences Expressed by Ordinal Vectors — Multi-Decision Maker) is a weighting multi-criteria decision-making (MCDM) method introduced by Gomes, L. F. A. M. de Mello, J. C. C. B. S. Costa, H. G. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a struc

addiction medicine

SASSI

The SASSI is a comprehensive self-report inventory designed to identify substance abuse and dependence through both direct and indirect assessment methods. Developed by Glenn Miller in 1997 and updated to the SASSI-3 format, it employs 'subtle' items that indirectly measure substance abuse risk without openly asking ab

psychology of religion

SBI

The Systems of Belief Inventory (SBI), developed by Holland, Currier, and Neimeyer in 2011, is a 15-item self-report measure designed to assess the coherence, flexibility, and adaptive function of an individual's worldview and meaning-making system. Originally validated in bereavement research, the SBI captures dimensi

decision making

SCHULZE

SCHULZE (Schulze Method — Beat-path Condorcet-consistent rank aggregation) is a aggregationoperator multi-criteria decision-making (MCDM) method introduced by Schulze, M. in 2011. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

operations management

SCOR Model

The Supply Chain Operations Reference Model is a standardized framework for supply chain management developed by the Supply Chain Council (now APICS) in 1996. SCOR provides a structured approach to identify, evaluate, and improve supply chain processes across organizations, regardless of industry. It integrates plannin

decision making

SD-WEIGHT

SD-WEIGHT (Standard Deviation Weight — objective weighting by column standard deviation) is a weight objective multi-criteria decision-making (MCDM) method introduced by Various in 1980. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

SECA

SECA (Simultaneous Evaluation of Criteria and Alternatives) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, rep

experimental design

Sensitivity Analysis with Six Sigma DMAIC

Sensitivity analysis integrated with Six Sigma DMAIC augments the classic Define-Measure-Analyze-Improve-Control cycle with formal quantification of how much each input variable contributes to output variation. By embedding local or global sensitivity indices inside the Analyze phase, practitioners move beyond correlat

decision making

SENSITIVITY-ANALYSIS

SENSITIVITY-ANALYSIS (Sensitivity Analysis — Systematic assessment of output variation w.r.t. input perturbations) is a ranking multi-criteria decision-making (MCDM) method introduced by Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. in 2004. It turns a decision matrix of alternatives scored on multiple criteri

decision making

SF-ARAS

SF-ARAS (Spherical extension of ARAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Kutlu Gündoğdu, F. Kahraman, C. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

SF-COCOSO

SF-COCOSO (SF-CoCoSo — Spherical extension of COCOSO) is a ranking multi-criteria decision-making (MCDM) method introduced by Kutlu Gündoğdu, F. Kahraman, C. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

SF-CODAS

SF-CODAS (Spherical extension of CODAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Karaşan, Boltürk & Kutlu Gündoğdu (book chapter); earlier Kutlu Gündoğdu-Kahraman 2019c JMVLSC in 2019 / 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reprodu

decision making

SF-COPRAS

SF-COPRAS (Spherical extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Kutlu Gündoğdu, F. Kahraman, C. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

decision making

SF-EDAS

SF-EDAS (Spherical extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Garg, H., Sharaf, I.M. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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