------------------------------------------------------------------------========================================================================              R  E  A  D  M  E         F  I  L  E========================================================================  The complete package consists of the following files :                -eps-dom.cpp		-inp		-input.h		-random.h		-Readme (this file)		-realcross.h		-realmut.h  The small descritption about these files are given below:  eps-dom.cpp  ~~~~~~~~~~~  This file consists of the main code for the implementation of the Epsilon  Based MOEA propsed by Dr.Deb et. al. in the paper titled "Towards a Quick   Computation of Well Spread Pareto-Optimal Solutions"                 - Deb, Mohan and Mishra (EMO-2003 Proceedings)                   Also available from http://www.iitk.ac.in/kangal/pub.htm                    (KanGAL Report Number 2003002)  This file has most of the functions (including the main() function). The number   of objective functions, the number of decision variables, the number of  constraints ,the actual function definitions and the actual constraints are defined  inside this file. The epsilon matrix is also defined in this file.  NOTE: (1) The dimension of the epsilon matrix is (1xM)             where M = No. of Objective functions        (2) The code is written for minimization cases. 	    For maximization, transform the	    problem into a minimization problem by multiplying by (-1).	      realcross.h  ~~~~~~~~~~~  Contains the implementation of the real parameter SBX crossover. For details,  please refer to Deb's 2001 book entitled `Multi-Objective Optimization   using Evolutionary Algorithms', Chichester: Wiley.  realmut.h  ~~~~~~~~~  Contains the implementation of polynomial mutation. For details, please  refer the above-mentioned book.  input.h  ~~~~~~~  Contains the function which takes the upper/lower bounds corresponding to each  decision variable. It also prompts for the GA parameters.  random.h  ~~~~~~~~  This file has an starts up the random number generator based on a seed value  (which is provided as an input)    inp  ~~~  A Sample input file. The current file corresponds to the 7-decision variable,   3-objective, 0-constraint DTLZ1 function.  Refer the following paper for complete and detailed description of the   problem:  Scalable multi-objective optimization test problems,                - K. Deb and L. Thiele and M. Laumanns and E. Zitzler          http://www.iitk.ac.in/kangal/pub.htm (Report No. 2001001) }--------------  Sample Input File --------------------0 1 // lower and upper bound of first decision variable0 10 10 10 10 10 1 // lower and upper bound of Seventh decision variable1.0    // Probability of crossover (keep 1.0)0.1428 // Probability of mutation (keep 1/number of variables)15  // SBX distribution index (keep between 5 to 20)20  // Mutation distriubution index (keep between 10 to 100)0.123  // Random seed (keep between 0.0 and 1.0)15000  // Number of generations (note that number of function eval.        //   is TWICE to this number)-----------------End of Sample Input File ------------------  H O W   T O  U S E   T H E   C O D E  ------------------------------------  The program is complied by the command (requires C++ complier)  c++ eps-dom.cpp  It can be executed by giving:  a.out  OR ./a.out  The inputs can be given from the console or can be redirected from   a file like:  a.out <inp   OR ./a.out <inp   O U T P U T    F I L E S     G E N E R A T E D  ---------------------------------------------  The following output are generated (all are with extension .out) after  sucessfull completion of the execution of the code.                 -archive.out		 -box_vectors.out		 -popltn.out		 -ar_variables.out  The small descritption about these files are given below:  archive.out  ~~~~~~~~~~~  This is the main output file. It contains the objective function values of  the various solutions in the final archive. Each line of the file corresponds  to a particular solution in the archive. Each column of the file represents  the various values obtained by the solutions in the final archive for a  particular objective function. So, the i-th row and j-th column would represent  the j-th objective function value of the i-th solution in the final arhcive.  ar_variables.out  ~~~~~~~~~~~~~~~~  This file contains the values of the decision variables corresponding to the  solutions in the final archive. Each line of the file corresponds  to a particular solution in the archive. Each column of the file represents  the various values obtained by the solutions in the final archive for a  particular decision variable. So, the i-th row and j-th column would represent  the j-th decision variable of the i-th solution in the final arhcive.  box_vectors.out  ~~~~~~~~~~~~~~~  This file contains the box vectors corresponding to the solutions in the final  archive. Each line represents all the box-vectors of a particular solution.  popltn.out  ~~~~~~~~~~  This file has a similar format as that of 'archive.out'. It contains the  objective function values of the various solutions in the final population.  Each line of the file corresponds to a particular solution in the population.For any bug or other information, please contact Kalyanmoy DebDepartment of Mechanical EngineeringIndian Institute of Technology KanpurKanpur, PIN 208016, IndiaE-mail: deb@iitk.ac.inhttp://www.iitk.ac.in/kangal/deb.htmDISCLAIMER: We do not take the responsibility of any bug in the codeor any of its malfunctioning in any particular problem.------------------------------------------------------------------------========================================================================