Related papers: Nature-Inspired Algorithms in Optimization: Introduction, Hybridization and Insights

URL: http://arxiv.org/abs/2401.00976v1
Date: Wed, 30 Aug 2023 11:33:22 GMT
Title: Nature-Inspired Algorithms in Optimization: Introduction, Hybridization and Insights
Authors: Xin-She Yang
Abstract summary: Benchmarking is important in evaluating the performance of optimization algorithms. This chapter focuses on the overview of optimization, nature-inspired algorithms and the role of hybridization.
Score: 1.6589012298747952
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Many problems in science and engineering are optimization problems, which may require sophisticated optimization techniques to solve. Nature-inspired algorithms are a class of metaheuristic algorithms for optimization, and some algorithms or variants are often developed by hybridization. Benchmarking is also important in evaluating the performance of optimization algorithms. This chapter focuses on the overview of optimization, nature-inspired algorithms and the role of hybridization. We will also highlight some issues with hybridization of algorithms.

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