文件列表:

nsga\nsga2code\crossover.h (1500, 2002-01-05)
nsga\nsga2code\decode.h (942, 2002-01-05)
nsga\nsga2code\dfit.h (3241, 2002-01-05)
nsga\nsga2code\func-con.h (2868, 2002-01-05)
nsga\nsga2code\init.h (774, 2002-01-05)
nsga\nsga2code\inp-b (60, 2002-01-05)
nsga\nsga2code\inp-r (59, 2002-01-05)
nsga\nsga2code\inp-rb (64, 2002-01-05)
nsga\nsga2code\input-binary (633, 2002-01-05)
nsga\nsga2code\input.h (7544, 2002-01-05)
nsga\nsga2code\input-rb+bin (885, 2002-01-05)
nsga\nsga2code\input-real (423, 2002-01-05)
nsga\nsga2code\keepaliven.h (12548, 2002-01-05)
nsga\nsga2code\mut.h (692, 2002-01-05)
nsga\nsga2code\nsga2.c (15616, 2002-01-05)
nsga\nsga2code\rancon.h (5314, 2002-01-05)
nsga\nsga2code\random.h (4011, 2002-01-05)
nsga\nsga2code\ranking.h (4297, 2002-01-05)
nsga\nsga2code\realcross2.h (3051, 2002-01-05)
nsga\nsga2code\realinit.h (838, 2002-01-05)
nsga\nsga2code\realmut1.h (1445, 2002-01-05)
nsga\nsga2code\realselect.h (2685, 2002-01-05)
nsga\nsga2code\report.h (3722, 2002-01-05)
nsga\nsga2code\roullette.h (1668, 2002-01-05)
nsga\nsga2code\select.h (2760, 2002-01-05)
nsga\nsga2code\uniformxr.h (1294, 2002-01-05)
nsga\nsga2code\nsga2.dsp (3387, 2010-01-29)
nsga\nsga2code\Debug\vc60.idb (33792, 2010-01-29)
nsga\nsga2code\Debug\vc60.pdb (45056, 2010-01-29)
nsga\nsga2code\Debug\nsga2.ilk (273592, 2010-02-27)
nsga\nsga2code\Debug\nsga2.exe (482816, 2010-02-27)
nsga\nsga2code\Debug\nsga2.sln (878, 2010-02-27)
nsga\nsga2code\Debug\nsga2.suo (7680, 2010-02-27)
nsga\nsga2code\Debug\BuildLog.htm (38258, 2010-02-27)
nsga\nsga2code\Debug\nsga2.exe.embed.manifest (406, 2010-02-27)
nsga\nsga2code\Debug\vc90.idb (52224, 2010-02-27)
nsga\nsga2code\Debug\vc90.pdb (53248, 2010-02-27)
nsga\nsga2code\Debug\nsga2.obj (108870, 2010-02-27)
nsga\nsga2code\Debug\nsga2.exe.embed.manifest.res (472, 2010-02-27)
nsga\nsga2code\Debug\nsga2.pdb (2190336, 2010-02-27)
... ...

moealib is a C++ library for multi-objective evolutionary algorithms. currently included moeas are: Niched Pareto Genetic Algorithm Nondominated Sorting Genetic Algorithm Pareto Tree Searching Genetic Algorithm Strength Pareto Evolutionary Algorithm Vector Evaluated Genetic Algorithm This library is mainly research-oriented rather than application oriented. It is designed together with my research work on MOEA, and actually one result of my work is a new algorithm, Pareto Tree Searching Genetic Algorithm, which is also included in the library. No separate and detailed documents are available now (maybe I will do it later.), though there are comments in each head or source file. Parameters to the moea can be set either by member functions or command line arguments. 'a.out --help' will give a detailed explanation for the way to enter command line arguments. See examples in knapsack/ about how a meoa program should be written. makefiles for moealib and for example programs in knapsack/ are also provided. assert() is used frequently in all my source codes, and it aims both at debugging and at commenting. Accordingly, there are two versions both for moealib and for example programs, one optimized version(disabling assert()), the other debugging version. Please see each makefile for details. I did all the work under linux, using emacs and g++ complier(thanks to the authors). Below is a list of all the head files in moealib. AlleleStr.h allele string class. Assign.h class for fitness assign. Beware not all meoas use an explicit assign class. Bin2DecGenome.h float representation class 'is-a' IND class and 'has-a' mapping object. Genome.h IND class 'is-a' AlleleStr (genome information) and 'has-a' ObjectiveVector. Grid_Loc.h binary string encoded location for grid(node) in Pareto Tree Searching GA. MOEA.h base class for multi-objective evolutionary algorithms. NPGA.h Niched Pareto GA. NSGA.h Nondominated Sorting GA Normalizer.h Vector class 'has-a' object of this class to do metric normalization. ObjectiveVector.h add static member mM to Vector class to indicate minimize or maximize. PTSGA.h Pareto Tree Searching GA. PTree.h Pareto Tree class. similar to population in other moeas. PTreeNode.h node class for Pareto Tree. ParameterList.h MOEA 'has-a' object of this class to (mainly) do command line parsing. Pareto.h The base class for nearly all classes here. Defining static members(mM, etc.) Population.h container class for individuals Random.h random generator defined as macro. copied from genesis. Reduction.h class doing population reduction. Only used by SPEA. SPEA.h Strength Pareto Evolutionary Algorithm. Select.h selection class VEGA.h Vector Evaluated GA Vector.h class template for vector. Author: Xianming Chen Computer Science Department Nankai University, Tianjin, P.R.*** email: xchen@nankai.edu.cn March 21, 2001, Xianming Chen.

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