GeneHunter  基因演算法軟體

Overview
GeneHunter is a powerful software solution for optimization problems which utilizes a state-of-the-art genetic algorithm methodology. GeneHunter includes an Excel Add-In which allows the user to run an optimization problem from Microsoft Excel, as well as a Dynamic Link Library of genetic algorithm functions that may be called from programming languages such as Microsoft® Visual Basic or C.
　

How Does GeneHunter Work?
GeneHunter solves optimization problems in the same way. It will create a population of possible solutions to the problem. The individuals in this population will carry chromosomes which are the values of variables of the problem.
GeneHunter actually solves your problem by allowing the less fit individuals in the population to die, and selectively breeding the most fit individuals. The process is called selection, as in selection of the fittest. GeneHunter takes two individuals and mates them (crossover), the offspring of the mated pair will receive some of the characteristics of the mother and some of the father.

In nature, offspring often have some slight abnormalities, called mutations. Usually, these mutations are disabling and inhibit the ability of the offspring to survive, but once in a while, they improve the fitness of the individual. GeneHunter occasionally causes mutations to occur.

As GeneHunter mates fit individuals and mutates some, the population undergoes a generation change. The population will then consist of offspring plus a few of the older individuals which GeneHunter allows to survive to the next generation. These are the most fit in the population, and we will want to keep them breeding. These most fit individuals are called elite individuals. After dozens or even hundreds of "generations," a population eventually emerges wherein the individuals will solve the problem very well. In fact, the most fit (elite) individual will be an optimum or close to optimum solution.

GeneHunter works in two ways. It's callable from Microsoft Excel spreadsheets, and accessible via function calls in a Dynamic Link Library (DLL). The function calls -- unique to GeneHunter -- are similar to the neural network function calls in NeuroWindows, Ward System Group's neural net DLL for Windows.

Solutions
After GeneHunter mates fit individuals and mutates some, the population undergoes a generation change. At this point, the population consists of offspring plus a few of the older individuals which GeneHunter allows to survive to the next "generation" because they are the fittest in the population. These fittest individuals are called elite individuals.

After dozens or even hundreds of "generations", a population eventually emerges whose individuals solve the target problem very well. In fact, the fittest (elite) individual will be an optimum or close to optimum solution.

The processes of selection, crossover, and mutation are called genetic operators. GeneHunter has several other genetic operators. One, diversity, allows additional but very slight mutations of the population. Another, extinction, is like a catastrophe that destroys most of the population (all but the elite individuals) and refreshes it with a large set of new individuals. GeneHunter sometimes causes extinction when so much inbreeding takes place that no offspring are fitter than their parents for many generations. (Extinction is only available in the DLL form of GeneHunter, not in the Excel interface.)

　

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