hyeonjang / numerical-optimization Goto Github PK

Github repo for the 2021 2nd semester numerical optimization assignments

• Report1

1. Implementation and Performance Comparision of the root finding methods (bisection, Newton's, secant, regular falsi)

• Report2

1. Implementation and Performance Comparision of the unimodal bracketing methods (Fibonacci, Golden section)
2. Implementation of the seeking bound algorithm

• Report3

1. Implementation and Performance Comparision of the multivariative methods (Nelder-Mead, Powell's)
2. Implementation of the termination conditions

• Report4

1. Implementation and Performance Comparision of the multivariative methods (the method of steepest descent, Newton's method, Quasi-Newton's method (SR1, BFGS))

• Report5

1. Implementation and Performance Comparision of the Conjugate Gradient methods (linearCG, nonlinearCG (CG-FR, CG-PR, CG-HS))

• Report6

1. Implementation of the Least Square Methods (Gauss-Newton's and LM (Levenberg-Marquardt))

• Report7

1. Implementation of the Genetic Algorithm and Performance comparison within the value of parameters

• clang-9
• cmake

Build description

1. Eigen 3.3.7
2. googletest (for testing)
3. googlebenchmark (for benchmarking)
4. Gnuplot & Gnuplot-iostream & boost (for plotting)

1. Clone the repo

   git clone --recursive https://github.com/hyeonjang/numerical-optimization.git

2. CMake build

   mkdir build
   cd build
   cmake ..
   make . -j 8

3. Run unter the build directory

   /build/test/hw#_test
   /build/benchmark/hw#_benchmark
   /build/plot/hw#_plot

Distributed under the MIT License. See LICENSE for more information.

hyeonjang - @gmail - [email protected]