Significance Relations for the Benchmarking of Meta-Heuristic Algorithms [PDF]
2013 13th International Conference on Intellient Systems Design and Applications, 2013 The experimental analysis of meta-heuristic algorithm performance is usually based on comparing average performance metric values over a set of algorithm instances.
Mario Koeppen, Kei Ohnishi
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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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Surrogate-Assisted Hybrid Meta-Heuristic Algorithm with an Add-Point Strategy for a Wireless Sensor Network [PDF]
Entropy, 2023 Meta-heuristic algorithms are widely used in complex problems that cannot be solved by traditional computing methods due to their powerful optimization capabilities. However, for high-complexity problems, the fitness function evaluation may take hours or
Jeng-Shyang Pan +4 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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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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A Self-Parametrization Framework for Meta-Heuristics [PDF]
Mathematics, 2022 Even while the scientific community has shown great interest in the analysis of meta-heuristics, the analysis of their parameterization has received little attention. It is the parameterization that will adapt a meta-heuristic to a problem, but it is still performed, mostly, empirically. There are multiple parameterization techniques; however, they are
André S. Santos +2 more
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A Hybrid Artificial Grasshopper Optimization (HAGOA) Meta-Heuristic Approach: A Hybrid Optimizer For Discover the Global Optimum in Given Search Space [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2019 Meta-heuristic algorithms are used to get optimal solutions in different engineering branches. Here four types of meta-heuristics algorithms are used such as evolutionary algorithms, swarm-based algorithms, physics based algorithms and human based ...
Brahm Prakash Dahiya +2 more
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An Application of Heuristic and Meta Dendral Expert System [PDF]
ITM Web of Conferences, 2022 A mobile application is the best way to reach the largest possible number of users, and it is a smart idea and dealing with it is very easy. In the Corona pandemic, many Mobile applications appeared that helped the community with the necessary ...
Tawafak Ragad M +2 more
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