<![CDATA[Genetic algorithms are search algorithms based on natural selection mechanisms and natural genetics. Initially genetics is used as the algorithm for searching the optimal parameters. But in its development, genetic algorithms can be applied to various other problems such as learning, forecasting, searching for the shortest path and so on. Genetic algorithm is widely used in the field of soft computing to obtain optimal parameter values on neural networks as well as fuzzy systems (Suyanto, 2011). Optimization and search techniques based on genetic principles are called genetic algorithms. The genetic algorithm allows a population of many individuals to evolve based on certain selection rules to the maximum fitness state (minimal cost function). Genetic algorithm is one solution that can be used in solving the problem of scheduling the course. The genetic algorithm is based on the mechanisms of natural selection known as biological evolutionary processes such as natural selection, crossover and mutation. Application of this algorithm will save time and cost incurred by the parties.Keywords: genetic algorithm, scheduling, soft computing]]>
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