Biology-Derived Algorithms in Engineering Optimization

TL;DR

This paper reviews biology-inspired algorithms like genetic algorithms and neural networks, emphasizing their significance in engineering optimization and their basis in natural biological processes.

Contribution

It provides an overview of various biologically inspired algorithms and discusses their applications in engineering optimization.

Findings

Biologically inspired algorithms are crucial in solving complex engineering problems.

These algorithms are based on natural evolution and biological activities.

They have broad applications across scientific disciplines.

Abstract

Biology-derived algorithms are an important part of computational sciences, which are essential to many scientific disciplines and engineering applications. Many computational methods are derived from or based on the analogy to natural evolution and biological activities, and these biologically inspired computations include genetic algorithms, neural networks, cellular automata, and other algorithms.