Results 61 to 70 of about 177,718 (299)

Challenges and Opportunities for Applying Meta-Heuristic Methods in Vehicle Routing Problems: A Review

open access: yesEngineering Proceedings
The Vehicle Routing Problem (VRP) is related to determining the route of several vehicles to distribute goods to customers efficiently and minimize transportation costs or optimize other objective functions.
Wayan Firdaus Mahmudy   +2 more
doaj   +1 more source

Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

open access: yesComputers, 2022
Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely
Tara Othman Qadir Saraf   +2 more
doaj   +1 more source

Time series predictive analysis based on hybridization of meta-heuristic algorithms [PDF]

open access: yes, 2018
This paper presents a comparative study which involved five hybrid meta-heuristic methods to predict the weather five days in advance. The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial ...
Ernawan, Ferda   +4 more
core  

Meta-Heuristics: An Overview [PDF]

open access: yes, 1996
Meta-heuristics are the most recent development in approximate search methods for solving complex optimization problems, that arise in business, commerce, engineering, industry, and many other areas. A meta-heuristic guides a subordinate heuristic using concepts derived from artificial intelligence, biological, mathematical, natural and physical ...
Ibrahim H. Osman, James P. Kelly
openaire   +1 more source

Advanced Experiment Design Strategies for Drug Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang   +3 more
wiley   +1 more source

A Search-Based Test Data Generation Method for Concurrent Programs

open access: yesInternational Journal of Computational Intelligence Systems, 2020
Concurrent programs are being widely adopted in development of multi-core and many-core processors. However, these types of programs present some features such as concurrency, communication and synchronization which make their testing more challenging ...
Seyed Mohsen Mirhosseini   +1 more
doaj   +1 more source

Investigating Evaluation Measures in Ant Colony Algorithms for Learning Decision Tree Classifiers [PDF]

open access: yes, 2015
Ant-Tree-Miner is a decision tree induction algorithm that is based on the Ant Colony Optimization (ACO) meta- heuristic. Ant-Tree-Miner-M is a recently introduced extension of Ant-Tree-Miner that learns multi-tree classification models.
Abdelbar, Ashraf M.   +2 more
core   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

open access: yesAdvanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker   +3 more
wiley   +1 more source

Mud Ring Algorithm: A New Meta-Heuristic Optimization Algorithm for Solving Mathematical and Engineering Challenges

open access: yesIEEE Access, 2022
This paper proposes a new meta-heuristic optimization algorithm, namely Mud Ring Algorithm (MRA) that mimics the mud ring feeding behaviour of bottlenose dolphins in the Atlantic coast of Florida.
Abeer S. Desuky   +4 more
doaj   +1 more source

Training a Feed-forward Neural Network with Artificial Bee Colony Based Backpropagation Method

open access: yes, 2012
Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex problem. Artificial
Das, Achintya   +2 more
core   +1 more source

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