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Heuristics and Metaheuristic Optimization Algorithms
2020The concept of optimization is widely used to locate the optimum solution for different mathematical problems.
Dipti Kapoor Sarmah +2 more
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Mathematics and Computers in Simulation, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jeng-Shyang Pan +4 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jeng-Shyang Pan +4 more
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Thermal Exchange Metaheuristic Optimization Algorithm
2021This chapter consists of two parts. In the first part, the recently developed optimization algorithm based on Newton’s law of cooling is presented, which is called Thermal Exchange Optimization (TEO) algorithm [1]. In the second part, the improved version of TEO is named as Improved TEO and abbreviated as ITEO [2] is presented.
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Gene Clustering Using Metaheuristic Optimization Algorithms
International Journal of Applied Metaheuristic Computing, 2015Gene clustering is a familiar step in the exploratory analysis of high dimensional biological data. It is the process of grouping genes of similar patterns in the same cluster and aims at analyzing the functions of gene that leads to the development of drugs and early diagnosis of diseases.
P. K. Nizar Banu, S. Andrews
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Metaheuristic Algorithm for Wellbore Trajectory Optimization
2019 1st International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), 2019A variety of possible well types and so many complex drilling variables and constraints make the wellbore optimization problem a very challenging work. Several types of well are listed as directional wells, horizontal wells, redrilling wells, complex structure wells, cluster wells, and extended reach wells etcetera.
Kallol Biswas +3 more
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Parameter Meta-optimization of Metaheuristic Optimization Algorithms
2012The quality of a heuristic optimization algorithm is strongly dependent on its parameter values. Finding the optimal parameter values is a laborious task which requires expertise and knowledge about the algorithm, its parameters and the problem. This paper describes, how the optimization of parameters can be automated by using another optimization ...
Christoph Neumüller +3 more
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Metaheuristic Algorithms in IoT: Optimized Edge Node Localization
2022In this study, a new hybrid method is proposed by using the advantages of Grey Wolf Optimizer (GWO) and Moth-Flame Optimization (MFO) algorithms. The proposed hybrid metaheuristic algorithm tries to find the near-optimal solution with high efficiency by using the advantage of both algorithms.
Farzad Kiani, Amir Seyyedabbasi
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A new metaheuristic algorithm: car tracking optimization algorithm
Soft Computing, 2017Over the last decade, several metaheuristic algorithms have emerged to solve numerical function optimization problems. Since the performance of these algorithms presents a suboptimal behavior, a large number of studies have been carried out to find new and better algorithms.
Jian Chen, Hui Cai, Wei Wang
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Vortex Swarm Optimization: New Metaheuristic Algorithm
2020This paper proposes a new swarm intelligence algorithm called vortex swarm optimization, inspired from vortex collective behavior where particles move around a common known center, they cover all the directions so they play as alarm system where any individual at any direction see the target (resources, predator…etc.) it informs other individuals to ...
Ahmed Sabry A. Elrahman, Hesham A. Hefny
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Plant intelligence based metaheuristic optimization algorithms
Artificial Intelligence Review, 2016Classical optimization algorithms are insufficient in large scale combinatorial problems and in nonlinear problems. Hence, metaheuristic optimization algorithms have been proposed. General purpose metaheuristic methods are evaluated in nine different groups: biology-based, physics-based, social-based, music-based, chemical-based, sport-based ...
Sinem Akyol, Bilal Alatas
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