Results 11 to 20 of about 87,787 (275)
A systematic review of meta-heuristic algorithms in IoT based application
Array, 2022 Internet-of-Things (IoT) has gained quick popularity with the evolution of technologies such as big data analytics, block-chain, artificial intelligence, machine learning, and deep learning.
Vivek Sharma, Ashish Kumar Tripathi
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Alexandria Engineering Journal, 2023 Meta heuristics is an optimization approach that works as an intelligent technique to solve optimization problems. Evolutionary algorithms, human-based algorithms, physics-based algorithms and swarm intelligence are categorized under meta-heuristic ...
Othman Waleed Khalid +2 more
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Meta-heuristic algorithms in car engine design: a literature survey [PDF]
IEEE Transactions on Evolutionary Computation, 2015 Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy.
Tayarani-N, Mohammad-H. +2 more
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Flood susceptibility mapping using meta-heuristic algorithms
Geomatics, Natural Hazards & Risk, 2022 Flood is a common global natural hazard, and detailed flood susceptibility maps for specific watersheds are important for flood management measures. We compute the flood susceptibility map for the Kaiser watershed in Iran using machine learning models ...
Alireza Arabameri +7 more
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Review of conventional metaheuristic techniques for resource-constrained project scheduling problem [PDF]
Journal of Project Management, 2022 This paper is concerned with an overview of the Resource-Constrained Project Scheduling Problem (RCPSP) and the conventional meta-heuristic solution techniques that have attracted the attention of many researchers in the field.
Amir Golab +3 more
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A comprehensive review on meta-heuristic algorithms and their classification with novel approach
Journal of Applied Research on Industrial Engineering, 2021 Conventional and classical optimization methods are not efficient enough to deal with complicated, NP-hard, high-dimensional, non-linear, and hybrid problems.
Hojatollah Rajabi Moshtaghi +2 more
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Cost-Aware and Energy-Efficient Task Scheduling Based on Grey Wolf Optimizer [PDF]
Journal of Mahani Mathematical Research, 2023 One of the principal challenges in the cloud is the task scheduling problem. Appropriate task scheduling algorithms are needed to achieve goals such as load balancing, minimum cost, minimum energy consumption, etc.
Reyhane Ghafari, Najme Mansouri
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Advances in meta-heuristic methods for large-scale black-box optimization problems
Zhongguo Jianchuan Yanjiu, 2021 The optimal design of complex engineering equipment usually faces high-complexity, high-dimensional optimization problems – the so-called "large-scale black-box optimization problems (LBOPs)" – which are characterized by unavailable mathematical ...
Puyu JIANG +3 more
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Comparison of Recent Meta-Heuristic Optimization Algorithms Using Different Benchmark Functions
Journal of Mathematical Sciences and Modelling, 2022 Meta-heuristic optimization algorithms are used in many application areas to solve optimization problems. In recent years, meta-heuristic optimization algorithms have gained importance over deterministic search algorithms in solving optimization problems.
Mahmut Dirik
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Metaheuristic Algorithms in Optimizing Deep Neural Network Model for Software Effort Estimation
IEEE Access, 2021 Effort estimation is the most critical activity for the success of overall solution delivery in software engineering projects. In this context, the paper’s main contributions to the literature on software effort estimation are twofold. First, this
Muhammad Sufyan Khan +5 more
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