Results 71 to 80 of about 11,699,218 (181)

Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information [PDF]

, 2022
The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the intuitionistic fuzzy sets combines the classical decision method is in its research and application is attracting attention.
Cai, Qiang, Wei, Guiwu, Liao, Ningna, Wang, Jing   +3 more
core  

Simulation-Based EDAs for Stochastic Programming Problems

, 2020
With the rapid growth of simulation software packages, generating practical tools for simulation-based optimization has attracted a lot of interest over the last decades. In this paper, a modified method of Estimation of Distribution Algorithms (EDAs) is
Abdel-Rahman Hedar, Alaa Abdel-Hakim, Amira Allam   +2 more
core   +1 more source

Data-driven sustainable supply chain management with MEREC-EDAS approach using bipolar fuzzy credibility numbers

Alexandria Engineering Journal
This paper presents the novel concept of bipolar fuzzy credibility numbers (BFCNs) which is a robust extension of bipolar fuzzy numbers (BFNs). The BFCNs integrate credibility measures to effectively manage bipolarity and vagueness.
Muhammad Riaz, Nabiah Mazher, Asia Tahir, Muhammad Aslam, Dragan Pamucar, Vladimir Simic   +5 more
doaj   +1 more source

Regularized k-order Markov models in EDAs

, 2012
k-order Markov models have been introduced to estimation of distribution algorithms (EDAs) to solve a particular class of optimization problems in which each variable depends on its previous k variables in a given, fixed order.
Karshenas, Hossein, Bielza Lozoya, María Concepción, Santana, Roberto, Larrañaga Múgica, Pedro María   +3 more
core   +1 more source

PERBANDINGAN METODE ADDITIVE RATIO ASSESSMENT (ARAS) DAN EVALUATION BASED ON DISTANCE FROM AVERAGE SOLUTION (EDAS) DALAM PEMILIHAN PERUSAHAAN JASA PENGIRIMAN DI KOTA TERNATE

ARAS and EDAS are two multi-criteria methods and are included in the MCDM method. The aim of this research is to build a decision support system using the ARAS and EDAS methods in order to compare the sensitivity of the ARAS method and the EDAS method ...
S Sudirman, Zuniar, Fuad, Achmad, Do. Abdullah, Saiful, A.HI. Usman, Alfanugrah   +3 more
core   +1 more source

Investigating the Potential of Evaluation Based on Distance from Average Solution (EDAS) Method in Crisp and Fuzzy Environments for Solving Building Energy Consumption Optimisation Multiple Attribute Decision-Making (MADM) Problems

Sustainable selection of the best energy consumption optimisation strategies for buildings, whether active or passive, is a complex task due to the existence of several criteria.
Balali, Amirhossein, Yunusa-Kaltungo, Akilu; id_orcid   +1 more
core   +1 more source

A Novel Extended EDAS in Minkowski Space (EDAS-M) Method for Evaluating Autonomous Vehicles [PDF]

Studies in Informatics and Control, 2019
Edmundas Kazimieras ZAVADSKAS, Željko STEVIĆ, Zenonas TURSKIS, Milovan TOMAŠEVIĆ   +3 more
openaire   +1 more source

A novel approach employing hesitant intuitionistic fuzzy linguistic Einstein aggregation operators within the EDAS approach for multicriteria group decision making

Heliyon
The Evaluation based on Distance from Average Solution (EDAS) is a multi-criteria decision analysis (MCDA) technique that uses various distances from average values to make decisions.
Shahzad Faizi, Wojciech Sałabun, Mubashar Shah, Tabasam Rashid   +3 more
doaj   +1 more source

Application of Decision-Making Support Model in the Operations Planning Process at the Tactical Level

Vojenské rozhledy
The paper is focused on research of military operations planning with the purpose of defining an efficient decision-making model at the tactical level for brigade-level offensive operation.
Marko Radovanović, Miša Živković, Marko Crnogorac   +2 more
doaj   +1 more source

Component weighting functions for adaptive search with EDAs

, 2008
This paper introduces the component weighting approach as a general optimization heuristic to increase the likelihood of escaping from local optima by dynamically modifying the fitness function.
Jose A. Lozano, Santana Hermida, Roberto, Larrañaga Múgica, Pedro María, Lozano Alonso, José Antonio, Pedro Larranaga, Roberto Santana   +5 more
core   +1 more source