Parallelcoding.com

Central Force Optimization (CFO) is a new and interesting optimization method that has been developed by Richard A. Formato. The most interesting aspect of CFO is that it is fully deterministic unlike PSO, GA, AIS, or any of the other PIS based techniques.

The papers that he has produced on the topic can be found at:

1. Are Near Earth Objects the Key to Optimization Theory?
2. Central Force Optimization: A New Metaheuristic with Applications in Applied Electromagnetics
3. Central Force Optimization: A New Nature Inspired Computational Framework for Multidimensional Search and Optimization
4. Central Force Optimization: A New Deterministic Gradient -like Optimization  Metaheuristic
5. Comparative Results: Group Search Optimizer and Central Force Optimization
6. Pseudorandomness in Central Force Optimization
7. Central Force Optimization Applied to the PBM Suite of Antenna Benchmarks

And, for all of those interested, click here to download my C++ implementation.

In pursuing some of my research as of late, I needed to use Particle Swarm Optimization. All I wanted was some simple code for both Real and Binary PSO – but I couldn’t find anything I like! So, I’m providing a file containing both along with the RNG that I used. Please be aware that this code has not been refined. It’s clear, but rather ugly.

Particle Swarm Optimization Code

Mersenne Twister

To my very own surprise I have not written a post since November! How crazy is that! The main reason of this has been the utter business of pursuing my PhD. What a crazy semester it was! So what have I accomplished in this first semester? It can be divided into 3 sections: Classes, Projects, and Papers.

As for classes, I completed two: Artificial Intelligence and The Smart Grid. Both were highly interesting courses and the hard work paid off as well – I received an A- and an A in the courses! The Artificial Intelligence course was very interesting and covered a vast amount of AI topics. The class was taught by Dr. Gursel Serpen. The Smart Grid class was taught by my own advisor, Dr. Lingfeng Wang, and was a very solid and thorough introduction to alternative energy systems and the smart grid.

Projects and Papers have a bit of an overlap. I have posted my AI paper here – “Survey of the Applications of Articial Intelligence Techniques to the Sudoku Puzzle” – but I will not be posting my other 3 papers until I am aware of their submission status.

Through the entire semester I learned a lot. During the coming semester I will be working with biologically inspired computing techniques, optimization, the smart grid, and high performance computing. I’ll keep you all updated!