Journal Article10.1016/J.ASOC.2017.11.043
Volleyball Premier League Algorithm
267
TL;DR: Results show that the VPL algorithm possesses a strong capability to produce superior performance over the other well-known metaheuristic algorithms and is effectively applicable to solve problems with complex search space.
read more
About: This article is published in Applied Soft Computing. The article was published on 01 Mar 2018. The article focuses on the topics: Firefly algorithm & Metaheuristic.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Aquila Optimizer: A novel meta-heuristic optimization algorithm
Laith Abualigah,Dalia Yousri,Mohamed Abd Elaziz,Ahmed A. Ewees,Mohammed A. A. Al-qaness,Amir H. Gandomi +5 more
TL;DR: From the experimental results of AO that compared with well-known meta-heuristic methods, the superiority of the developed AO algorithm is observed.
1.7K
Henry gas solubility optimization: A novel physics-based algorithm
TL;DR: A novel metaheuristic algorithm named Henry gas solubility optimization (HGSO), which mimics the behavior governed by Henry’s law to solve challenging optimization problems, provides competitive and superior results compared to other algorithms when solving challenging optimize problems.
910
A survey on new generation metaheuristic algorithms
TL;DR: In this survey, fourteen new and outstanding metaheuristics that have been introduced for the last twenty years other than the classical ones such as genetic, particle swarm, and tabu search are distinguished.
748
Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019)
TL;DR: In this article, an extensive literature review on solving feature selection problem using metaheuristic algorithms which are developed in the ten years (2009-2019) is presented, and a categorical list of more than a hundred metaheuristics algorithms is presented.
References
Genetic algorithms in search, optimization and machine learning
David E. Goldberg
- 01 Jan 1989
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
58.6K
•Book
Genetic algorithms in search, optimization, and machine learning
David E. Goldberg
- 01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
•Book
Adaptation in natural and artificial systems
John H. Holland
- 01 Jan 1975
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
John H. Holland
- 01 May 1992
TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
16.6K