Global-Optimization-HAGCS

Introduction

A new global optimization algorithm developed by using gradient infromation, multiple search strategies, and parameters self-adaptation.

HAGCS is desgined for the objective functions whose gradient is readily available. Essentially, the HAGCS algorithm is based on the Cuckoo search [CS, 1] algorithm.

Installation

addpath(genpath("./WZDOM"));

Test

1. View the animation of optimization process (run test_global_optimization/testShowAnimation.m )

Compare CS with HAGCS on the Drop Wave test function (bigger population size):

Compare CS with HAGCS on the Rastrigin test function:

Compare CS with HAGCS on the Rastrigin test function (smaller population size):

Compare CS with HAGCS on the Schwefel test function:

Compare CS with HAGCS on the Schwefel's P2.22 test function:

1. To compare the success rate, convergence speed of different algorithms, please run ./test_global_optimization/testCompareMethodsFinal.m

References

1 Xin-She Yang and Suash Deb. Cuckoo search via levy flights. In 2009 World Congress on Nature Biologically Inspired Computing (NaBIC), pages 210-214, Dec 2009.