Nature-Inspired Algorithms in Optimization: Introduction, Hybridization and Insights
This is an incremental review chapter for researchers in optimization and computational science, summarizing existing methods without introducing new results.
The chapter provides an overview of optimization problems and nature-inspired metaheuristic algorithms, focusing on their hybridization and benchmarking for performance evaluation.
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.