Jelajahi sains berdasarkan metode, bidang, dan bukti.

PIF-MARCOS

PIF-MARCOS (PiF-MARCOS — Picture extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIF-MOORA

PIF-MOORA (PiF-MOORA — Picture extension of MOORA) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIF-SAW

PIF-SAW (PiF-SAW — Picture extension of SAW) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIF-TODIM

PIF-TODIM (PiF-TODIM — Picture extension of TODIM) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIF-TOPSIS

PIF-TOPSIS (PiF-TOPSIS — Picture extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIF-VIKOR

PIF-VIKOR (PiF-VIKOR — Picture extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIF-WASPAS

PIF-WASPAS (PiF-WASPAS — Picture Fuzzy extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Cuong, B. C., Kreinovich, V. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PIPRECIA

PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Stanujkić, D., Karabašević, D., Zavadskas, E. K., Turskis, Z., Maksimović, M. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structu

PIV

PIV (Proximity Indexed Value) is a ranking multi-criteria decision-making (MCDM) method introduced by Mufazzal, S. Muzakkir, S. M. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2018

PL-EDAS

PL-EDAS (Probabilistic Linguistic extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Pang, Q. Wang, H. Xu, Z. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2016

PL-MABAC

PL-MABAC (Plithogenic MABAC (with BWM weighting and Rough Number uncertainty)) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D. Ćirović, G. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2015

PL-MARCOS

PL-MARCOS (Probabilistic Linguistic extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Wang, J., Wei, G., Wei, C., Wei, Y. in 2023. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2023

PL-MULTIMOORA

PL-MULTIMOORA (Probabilistic Linguistic extension of MULTIMOORA) is a ranking multi-criteria decision-making (MCDM) method introduced by Wu, X. Liao, H. Xu, Z. S. Hafezalkotob, A. Herrera, F. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2018

PL-TODIM

PL-TODIM (Probabilistic Linguistic extension of TODIM) is a ranking multi-criteria decision-making (MCDM) method introduced by Liu, P., Teng, F. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

PL-TOPSIS

PL-TOPSIS (Probabilistic Linguistic extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Lu, J., Wei, C. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2019

PL-VIKOR

PL-VIKOR (Probabilistic Linguistic extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Li, P., Liu, J., Wei, C. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2021

Plackett-Luce Model

The Plackett-Luce model is a probabilistic framework for analysing and predicting rank-ordered data. Introduced by Robin Plackett (1975) — building on R. Duncan Luce's earlier axiom of choice (1959) — it models the probability of any complete ranking of items as a sequential selection process, where each item's chance

1 sumber1975

Policy Scenario Dynamic Programming

Policy Scenario Dynamic Programming (PSDP) applies Bellman's recursive optimization framework to a set of pre-specified policy scenarios, enabling decision-makers to compare staged, sequential decisions under distinct future conditions. It decomposes a complex, multi-period policy choice into tractable sub-problems sol

2 sumber1957

Policy Scenario Genetic Algorithm

The Policy Scenario Genetic Algorithm applies evolutionary search to systematically explore large, combinatorial policy alternative spaces under multiple future scenarios. Rather than exhaustively enumerating options, it breeds successive generations of candidate policies, retaining those that perform well across scena

2 sumber1975

Policy Scenario Goal Programming

Policy Scenario Goal Programming (PSGP) integrates goal programming optimization with policy scenario analysis to evaluate how well competing policy objectives can be achieved under distinct future conditions. Decision-makers define multiple goals and several plausible policy scenarios, then solve a goal programming mo

2 sumber1961

Policy Scenario Integer Programming

Policy Scenario Integer Programming (PSIP) solves an integer programming model — where some or all decision variables must take whole-number values — separately under each of several distinct policy scenarios, then compares objective values, feasibility, and solution structures to identify which policy environment lead

2 sumber1950

Policy Scenario Particle Swarm Optimization

Policy Scenario Particle Swarm Optimization integrates Particle Swarm Optimization (PSO) with explicit policy scenario analysis. A swarm of candidate policy solutions is evaluated under multiple defined future scenarios, and PSO's velocity-position update rules guide the swarm toward solutions that perform well—or robu

2 sumber1995

Policy Scenario Queueing Simulation

Policy Scenario Queueing Simulation applies queueing theory and discrete-event simulation to evaluate two or more competing service or resource-allocation policies under realistic demand and capacity conditions. By holding the system structure constant and varying only the policy rules, analysts can directly compare th

2 sumber1909

soft computing

Possibility Theory

Possibility Theory is a mathematical framework for representing and reasoning under uncertainty, introduced by Lotfi Zadeh in 1978 and systematically developed by Didier Dubois and Henri Prade in their 1988 monograph. It uses possibility distributions — functions assigning a degree in [0,1] to each element of a univers

2 sumber1988

trauma psychology

Post-Traumatic Growth Inventory

The PTGI is a 21-item self-report scale measuring positive psychological outcomes and personal growth reported after trauma exposure. Developed by Tedeschi and Calhoun in 1996, the PTGI operationalizes the construct of posttraumatic growth (PTG)—the experience of positive life change accompanying psychological struggle

2 sumber1996

POWER-MEAN

POWER-MEAN (Weighted Power Mean (Hölder Mean)) is a aggregation multi-criteria decision-making (MCDM) method introduced by Hardy, G. H. Littlewood, J. E. Pólya, G. in 1934. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber1934

game theory

Principal-Agent Model

The Principal-Agent Model analyzes how a principal (e.g., owner, employer, policymaker) can incentivize an agent (e.g., manager, employee, firm) to act in the principal's interest when the agent has private information or can take hidden actions. Formalized by Jensen and Meckling in 1976, the model identifies agency co

2 sumber1976

PROB-ARAS

PROB-ARAS (Prob-ARAS — Stochastic extension of PROB-ARAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Zavadskas, E. K. Turskis, Z. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2010

PROBID

PROBID (Preference Ranking on the Basis of Ideal-Average Distance) is a ranking multi-criteria decision-making (MCDM) method introduced by Wang, Z., Rangaiah, G. P., Wang, X. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2021

PROMETHEE

PROMETHEE (PROMETHEE II — Preference Ranking Organisation METHod for Enrichment of Evaluations) is a outranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P., Vincke, Ph., Mareschal, B. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproduci

1 sumberadvanced1986

PROMETHEE-GAIA

PROMETHEE-GAIA combines two complementary tools: PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) for ranking alternatives through pairwise preference modeling, and GAIA (Geometric Analysis for Interactive Aid) for visual representation and sensitivity analysis. While PROMETHEE produces a r

2 sumber1986

PROMETHEE-I

PROMETHEE-I (PROMETHEE I — Preference Ranking Organisation METHod for Enrichment Evaluations I (partial ranking)) is a ranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P., Vincke, P., Mareschal, B. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structu

1 sumber1986

PROMETHEE-II

PROMETHEE-II (PROMETHEE II — Preference Ranking Organisation Method for Enrichment of Evaluations II) is a outranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P., Vincke, P. in 1985. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result

1 sumber1985

PROMETHEE-III

PROMETHEE-III (PROMETHEE III — Preference Ranking Organisation METHod for Enrichment Evaluations III (interval ranking)) is a outranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P. Vincke, P. Mareschal, B. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a

1 sumber1986

PROMETHEE-V

PROMETHEE-V (PROMETHEE V — PROMETHEE with Integer Programming Constraints) is a ranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P. Mareschal, B. in 1992. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber1992

PROMETHEE-VI

PROMETHEE-VI (PROMETHEE VI — Walking Weights Sensitivity) is a ranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P. Mareschal, B. in 1995. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber1995

PROSA-C

PROSA-C (Sustainability Criteria-Level Preference Ranking) is a ranking multi-criteria decision-making (MCDM) method introduced by Ziemba, P. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2019

PROXIMITY-WLC

PROXIMITY-WLC (Proximity-Adjusted WLC — spatially explicit weighted linear combination) is a ranking multi-criteria decision-making (MCDM) method introduced by Rinner, C.; Heppleston, A. in 2006. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2006

PSI

PSI (Preference Selection Index) is a ranking multi-criteria decision-making (MCDM) method introduced by Maniya, K., Bhatt, M. G. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber2010

operations research

Push-Relabel Algorithm

The Push-Relabel Algorithm, developed by Andrew V. Goldberg and Robert E. Tarjan in 1988, is a highly efficient method for computing maximum flow in networks. Unlike augmenting path methods, it maintains a preflow and uses local push and global relabeling operations to drive flow toward the sink, achieving superior wor

2 sumber1988

QR-ARAS

QR-ARAS (qR-ARAS — q-Rung Orthopair extension of ARAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-COCOSO

QR-COCOSO (qR-CoCoSo — q-Rung Orthopair extension of COCOSO) is a ranking multi-criteria decision-making (MCDM) method introduced by Kuvvetli, B. İ. (2023, JESD 11(4):1294-1309) — first published q-ROF CoCoSo application Peng, X. & Huang, H. (2020, TEDE 26(4):695-724) — algorithm source for q-ROF score function with he

1 sumber2023

QR-CODAS

QR-CODAS (qR-CODAS — q-Rung Orthopair extension of CODAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Naz, S., Akram, M., Sattar, A., Al-Shamiri, M. M. A. (2022, AIMS Math 7(9):17529-17569) — 2TLq-ROF CODAS family-adjacent variant (closest verified application paper) Keshavarz Ghorabaee, M.,

1 sumber2022

QR-COPRAS

QR-COPRAS (qR-COPRAS — q-Rung Orthopair extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-EDAS

QR-EDAS (qR-EDAS — q-Rung Orthopair extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-GRA

QR-GRA (qR-GRA — q-Rung Orthopair extension of GRA) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 1989. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber1989

QR-MABAC

QR-MABAC (qR-MABAC — q-Rung Orthopair extension of MABAC) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-MARCOS

QR-MARCOS (qR-MARCOS — q-Rung Orthopair extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-MOORA

QR-MOORA (qR-MOORA — q-Rung Orthopair extension of MOORA) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-PROMETHEE

QR-PROMETHEE (qR-PROMETHEE — q-Rung Orthopair extension of PROMETHEE) is a outranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-SAW

QR-SAW (qR-SAW — q-Rung Orthopair extension of SAW) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-TODIM

QR-TODIM (qR-TODIM — q-Rung Orthopair extension of TODIM) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-TOPSIS

QR-TOPSIS (qR-TOPSIS — q-Rung Orthopair extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-VIKOR

QR-VIKOR (qR-VIKOR — q-Rung Orthopair extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-WASPAS

QR-WASPAS (qR-WASPAS — q-Rung Orthopair extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

QR-WPM

QR-WPM (qR-WPM — q-Rung Orthopair extension of WPM) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. in 2017. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

optimization

Quadratic Programming

Quadratic Programming (QP) is a class of constrained mathematical optimization in which the objective function is quadratic and the constraints are linear. Formalized by Frank and Wolfe (1956) through their gradient-based feasible-direction algorithm, QP is foundational in operations research, finance, machine learning

1 sumber1956

QUALIFLEX

QUALIFLEX (QUALItative FLEXible multiple criteria method) is a ranking multi-criteria decision-making (MCDM) method introduced by Paelinck, J. H. P. in 1978. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

1 sumber1978