The CCO is much simpler and more robust optimization algorithm compared with particle swarm optimization (PSO), improved PSO (IPSO) and fruit fly optimization algorithm (FOA). Six numerical experiment ...

Numerical Optimization Algorithm Implementations A comprehensive collection of classical optimization algorithms implemented in Python, including gradient descent, Newton's method, interior point ...

During the winter vacation of 2016, I decided to make a change. I revisited some well-known optimization methods (e.g., Gradient Descent, Newton/Quasi-Newton Method, ALM, etc.), and made a series of ...

After being studied the expression of figure-counting methods, a special numerical method is presented to approach any given value. With a gradual decrease weight of each digit, under the given error, ...

Numerical simulation is a powerful tool for solving complex problems in science, engineering, and other fields. However, choosing the right numerical methods and algorithms can make a big ...

Nonlinear Least-Squares Optimization Levenberg-Marquardt Least-Squares Method (LEVMAR) The Levenberg-Marquardt method is a modification of the trust-region method for nonlinear least-squares problems ...

In the Main() method, the Solver object is instantiated for a population of eight solutions, each of which is a vector with six values. The population size value is a hyperparameter that must be ...

However, some optimization methods may not be easy to implement or validate, as they may require complex algorithms, specialized libraries, or proprietary software.

In recent years, memetic algorithms (also called hybrid genetic algorithms) have been proposed to increase the search efficiency of population based optimization algorithms . These methods are ...