One problem can have one or more solutions. If there are more than one solutions then we have to choose an optimal solutions. This is known as optimization process. There are many optimization techniques that can be used, such as: Entire Search, Grid Search, Evolution strategy (ES), and Genetic Algorithm (GA).
Among all techinques mentioned above, ES and GA have unique charateristics. They can use all existing solution's posibility to achieve an optimal one. ES emphasizes on mutation process whereas GA uses combination between recombination and mutation processes.
This series, Theory and Practice of Genetic Algorithm using C++, was divided into two topics :
1. Introduction into Genetic Algorithm
On this topic, we will discuss about the concept and basic algorithms used on GA.
Language : English
Price : 1 Euro (Rp. 10.000)
2. General Implementation of Genetic Algorithm
This topic explains how to combine the basic algorithms explained on the first topic to implement GA and its real example. It will be explained also the techniques and C++ programming's concept used on the example. The structure of source codes of the given example is actually the general structure. This means we can use this structure to solve other problems.
Language : English
Price : 1,5 Euro (Rp. 15.000)
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