% README.TXT file       (this file)                                 %
% ----------------------------------------------------------------- %
% Matlab Programs included the Appendix B in the book:              %
%  Xin-She Yang, Engineering Optimization: An Introduction          %
%                with Metaheuristic Applications                    %
%  Published by John Wiley & Sons, USA, July 2010                   %
%  ISBN: 978-0-470-58246-6,   Hardcover, 347 pages                  %
% ----------------------------------------------------------------- %
% Citation detail:                                                  %
% X.-S. Yang, Engineering Optimization: An Introduction with        %
% Metaheuristic Application, Wiley, USA, (2010).                    %
%                                                                   %
% http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470582464.html%
% http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470582464.html %
% ----------------------------------------------------------------- %
% ===== ftp://  ===== ftp://   ===== ftp:// ======================= %
% Matlab files ftp site at Wiley                                    %
% ftp://ftp.wiley.com/public/sci_tech_med/engineering_optimization  %
% ----------------------------------------------------------------  %

The Matlab programs included in this directory are zipped as a
single file: engineering_optimization_matlab.zip

These Matlab programs should always work in Octave, (except for
B7_spring.m and B7_pressure.m, as they use Matlab's toolbox)

Files included:
  Readme.txt      (this file)

  B1_ga.m       = genetic algorithm (works in both Matlab & Octave)
  B2_sa.m       = simulated annealing (both Matlab and Octave)
  B3_pso.m      = particle swarm optimization (Matlab and Octave)
  B4_hs.m       = harmony search (both Matlab and Octave)
  B5_firefly.m  = firefly algorithm (both Matlab and Octave)
  B6_cg.m       = conjugate gradient method (Matlab and Octave)
  B7_spring.m   = spring design optimization (Matlab only)
  B7_pressure.m = pressure vessel design optimization (Matlab only)

Constrained optimization (need Matlab version > 7.0 or later)
  sa_mincon.m   = constrained optimization (simulated annealing)
  fa_constrained_demo.m = nonlinear constrained optimization
                          (firefly algorithm)
  [Here the constraints are incorporated via the penalty method ]

----------------------------------------------------------------
Notes to users:
----------------------------------------------------------------
1) Here we have no intention to provide optimal/efficient
   implementations. In fact, these are demo codes only, as the
   main purpose is to show how each algorithm works.

2) These codes were mainly implemented in Matlab, they should
   also work in Octave; however, as the graph engine is
   different in Octave, some of the display may be different.
   In addition, for the constrained optimization codes,
   some function handles are used, you may need later version
   of Matlab, while the Octave has only limited ability of
   function handles at the moment.

3) As metaheuristic algorithms are stochastic in nature, 
   each run will usually produce slightly different results.
   Therefore, you should run the programs, say, 50 times,
   and then do the statistics and interpret them using
   statistical measures such as mean and standard deviations.

Notes:
 a) Matlab is the trademark of the MathWorks
    http://www.mathworks.com
 b) Octave is a GNU open source environment
    http://www.gnu.org/software/octave/
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