This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

A comprehensive genetic algorithm implementation for solving numerical optimization and combinatorial problems. This project provides a flexible framework for evolutionary computation with ...

Every manufacturing process should be operated with optimum machining conditions to achieve the goal of less machining time, less cost, as well as better quality of the product. The main objective of ...

Abstract: Based on simulated annealing algorithm and genetic algorithm, this study aims to provide an effective planting strategy to improve the efficiency of crop production in a village in the ...

In this study, we employ a genetic algorithm (GA), a class of bio-inspired optimization algorithms that mimic the process of natural selection and evolution. GAs are particularly suitable for complex, ...

Evolutionary optimization (EO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, EO can be used to train a neural network. EO is ...