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Multi-criteria decision making (MCDM) is necessary for choosing one from the available alternatives (or from the obtained Pareto-optimal solutions for multi-objective optimization), where the performance of each alternative is quantified…

Chemical Physics · Physics 2024-11-18 Zhiyuan Wang , Seyed Reza Nabavi , Gade Pandu Rangaiah

Multicriteria decision-making methods exhibit critical dependence on the choice of normalization techniques, where different selections can alter 20-40% of the final rankings. Current practice is characterized by the ad-hoc selection of…

Optimization and Control · Mathematics 2026-05-07 Juan B. Cabral , Alvaro Roy Schachner

Multi-Criteria Decision Making (MCDM) is a branch of operations research used in a variety of domains from health care to engineering to facilitate decision-making among multiple options based on specific criteria. Several R packages have…

Mathematical Software · Computer Science 2025-02-14 Annice Najafi , Shokoufeh Mirzaei

Real-life engineering optimization problems need Multiobjective Optimization (MOO) tools. These problems are highly nonlinear. As the process of Multiple Criteria Decision-Making (MCDM) is much expanded most MOO problems in different…

Software Engineering · Computer Science 2010-04-20 A. Mosavi

This chapter describes selected reference-type multi-criteria decision-making (MCDM) methods that rank alternatives by comparing them with one or more reference solutions derived from an alternatives-criteria matrix (ACM). After explaining…

Optimization and Control · Mathematics 2025-08-27 Zhiyuan Wang , Gade Pandu Rangaiah

Multi-criteria decision-making (MCDM) problems involve the evaluation of alternatives based on various minimization and maximization criteria. Similarly, efficiency evaluation (EA) methods assess decision-making units (DMUs) by analyzing…

Optimization and Control · Mathematics 2024-06-11 Fuh-Hwa Franklin Liu , Su-Chuan Shih

This chapter describes selected aggregation-type multi-criteria decision-making (MCDM) methods that convert an alternatives-criteria matrix (ACM) into a single performance score per alternative through additive, multiplicative or hybrid…

Optimization and Control · Mathematics 2025-09-09 Zhiyuan Wang , Gade Pandu Rangaiah

In this paper we explore several approaches for sampling weight vectors in the context of weighted sum scalarisation approaches for solving multi-criteria decision making (MCDM) problems. This established method converts a multi-objective…

Optimization and Control · Mathematics 2025-04-18 Aled Williams , Yilun Cai

With increases in population, there is a noticeable change across the world in pollution levels. Recently there has been growing demand for renewable energy operated devices boomed. Numerous reasons have led to such growth including lower…

Optimization and Control · Mathematics 2023-03-31 Mahak Bhatia , Aled Williams

Accelerating the renewable energy transition requires informed decision-making that accounts for the diverse financial, technical, environmental, and social trade-offs across different renewable energy technologies. A critical step in this…

Optimization and Control · Mathematics 2026-01-07 Ding Ding , Yang Li , Poh Ling Neo , Zhiyuan Wang , Chongwu Xia

The process of multiple criteria decision making (MCDM) is of determining the best choice among all of the probable alternatives. The problem of supplier selection on which decision maker has usually vague and imprecise knowledge is a…

Artificial Intelligence · Computer Science 2020-01-01 Rıdvan Şahin , Muhammed Yiğider

In multi-criteria decision making (MCDM) problems, ratings are assigned to the alternatives on different criteria by the expert group. In this paper, we propose a thermodynamically consistent model for MCDM using the analogies for…

Artificial Intelligence · Computer Science 2017-03-28 Mohit Verma , J. Rajasankar

Multi-Criteria Decision-Making (MCDM) techniques have found widespread application across diverse fields. The rapid evolution of MCDM has led to the development of hundreds of methods, each employing distinct approaches. However, due to…

Other Statistics · Statistics 2025-09-11 Nguyen Thi Thu Hien , Pham Huong Quynh , Vu Quang Minh

In this paper a multi-objective mathematical model has been used to optimize grinding parameters include workpiece speed, depth of cut and wheel speed which highly affect the final surface quality. The mathematical model of the optimization…

Other Computer Science · Computer Science 2022-03-15 Meysam Mahjoob

Multi-Criteria Decision Making~(MCDM) is widely applied in various fields, using quantitative and qualitative analyses of multiple levels and attributes to support decision makers in making scientific and rational decisions in complex…

Artificial Intelligence · Computer Science 2025-02-25 Hui Wang , Fafa Zhang , Chaoxu Mu

Robust Ordinal Regression (ROR) is a way of dealing with Multiple Criteria Decision Aiding (MCDA), by considering all sets of parameters of an assumed preference model, that are compatible with preference information given by the Decision…

Optimization and Control · Mathematics 2012-06-28 Salvatore Corrente , Salvatore Greco , Roman Slowinski

Multi-criteria decision analysis (MCDA) is a quantitative approach to the drug benefit-risk assessment (BRA) which allows for consistent comparisons by summarising all benefits and risks in a single score. The MCDA consists of several…

Methodology · Statistics 2021-07-27 Tom Menzies , Gaelle Saint-Hilary , Pavel Mozgunov

The TODIM method (an acronym in Portuguese for interactive and multiple criteria decision-making) with entropy weights is influenced by rank reversal, a phenomenon where the order of two alternatives changes following the addition of…

Optimization and Control · Mathematics 2025-09-11 Lisheng Jiang , Tianyu Zhang , Shiyu Yan , Ran Fang

Decision support methods from operations research are widely used to support complex planning decisions. Within the energy sector, energy system models (ESMs) applying modelling to generate alternatives (MGA) generate large sets of…

General Economics · Economics 2026-05-25 Emily Bergup , Jonas Finke , Sebastian Schär , Valentin Bertsch

Most successful stochastic black-box optimizers, such as CMA-ES, use rankings of the individual samples to obtain a new search distribution. Yet, the use of rankings also introduces several issues such as the underlying optimization…

Machine Learning · Statistics 2022-06-14 Maximilian Hüttenrauch , Gerhard Neumann
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