/GEO_OptimizationAlgorithms

Adaptive versions of the GEO optimization algorithm and its application in the conceptual project of space systems

Primary LanguageC#MIT LicenseMIT

STUDY TO INCREASE THE PERFORMANCE OF THE ADAPTIVE VERSION OF THE GEO ALGORITHM AND ITS APPLICATION IN THE CONCEPTUAL PROJECT OF SPACE SYSTEMS

This repository contains the algorithms developed during a master's thesis. The main focus of the work was to improve the evolutionary algorithm A-GEO, which was presented in the paper A new Adaptive Evolutionary Algorithm for Design Optimization (Barroca, 2019).

Project Status: Active. License lifecycle

Objectives   • Algorithms  

 

Objectives

  • Implement the parameter control mechanism of A-GEO in GEOvar, a variant of GEO, verifying this implementation using a set of test functions;
  • Change the encoding of the A-GEO design variables from binary to real, no longer requiring the definition of the number of bits encoding each variable;
  • Study how the design variables are perturbed in the real encoding, as well as how to perform several mutations on each variable in a single iteration;
  • Investigate the control mechanism for the parameter τ proposed for A-GEO, which may indicate other ways to control the parameter during search;
  • Explore ways to make A-GEOreal fully adaptive, without the need for parameter tuning;
  • Apply the improved algorithm in the search for automating the creation of solutions in a conceptual design of space systems;

 

Algorithms

Binary Encoding:

- GEO
- GEOvar
- A-GEO
- A-GEOvar
- A-GEO2var_5

Real Encoding:

- GEOreal1 (GEOreal1_M, GEOreal1_P, GEOreal1_A)
- GEOreal2 (GEOreal2_M_VO, GEOreal2_P_VO, GEOreal2_A_VO, GEOreal2_M_DS, GEOreal2_P_DS, GEOreal2_A_DS)
- GEOreal2_P_DS_UNI
- A-GEO2real1_AA
- A-GEO2real2_AA0
- A-GEO2real2_AA1
- A-GEO2real2_AA2
- A-GEO2real2_AA3