Parameter-Free Deterministic Global Search with Central Force Optimization

Details Parameter-Free Deterministic Global Search with Central Force Optimization Parameter-Free Deterministic Global Search with Central Force Optimization

2010-03-04

arxiv.org/abs/1003.1039v2

Computer Science

Other Computer Science

Scientific paper

This note describes a parameter-free implementation of Central Force Optimization for deterministic multidimensional search and optimization. The user supplies only one input: the objective function to be maximized, nothing more. The CFO equations of motion are simplified by assigning specific values to CFO's basic parameters, and this particular algorithmic implementation also includes hardwired internal parameters so that none is user-specified. The algorithm's performance is tested against a widely used suite of twenty three benchmark functions and compared to other state-of-the-art algorithms. CFO performs very well indeed. Includes important update 20 March 2010 addressing the issue of different probes coalescing into one.

Affiliated with

Also associated with

No associations

Rating

Parameter-Free Deterministic Global Search with Central Force Optimization does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Parameter-Free Deterministic Global Search with Central Force Optimization, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Parameter-Free Deterministic Global Search with Central Force Optimization will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-560154