Answers.Body: <p>There are numerous problems that can be solved with genetic algorithms or, more generally, with evolutionary algorithms (which includes also genetic programming and evolutionary strategies), even though they may not necessarily be the most efficient approach.</p>
  <p>Here are a few examples.</p>
  <ul>
  <li>Evolution of the topology of neural networks. This is called <a href="https://en.wikipedia.org/wiki/Neuroevolution" rel="nofollow noreferrer">neuroevolution</a>.</li>
  <li>Automatic test case generation (in particular, for self-driving cars). <a href="https://www.researchgate.net/profile/Alessio_Gambi/publication/335362266_AsFault_Testing_Self-Driving_Car_Software_Using_Search-Based_Procedural_Content_Generation/links/5d70bd4792851cacdb21a956/AsFault-Testing-Self-Driving-Car-Software-Using-Search-Based-Procedural-Content-Generation.pdf" rel="nofollow noreferrer">AsFault</a> is one specific example.</li>
  <li>Design of novel quantum computing algorithms. Specifically, genetic programming has been used to solve this problem (see <a href="https://www.researchgate.net/publication/244428002_Genetic_Programming_for_Quantum_Computers" rel="nofollow noreferrer">this reference</a> for more details).</li>
  <li>As an alternative to reinforcement learning algorithms to solve RL problems. Specifically, evolution strategies have been successfully used in this case (see <a href="https://openai.com/blog/evolution-strategies/" rel="nofollow noreferrer">this</a>).</li>
  </ul>
  <p>There is a Wikipedia article that lists many other applications of genetic algorithms: <a href="https://en.wikipedia.org/wiki/List_of_genetic_algorithm_applications" rel="nofollow noreferrer">List of genetic algorithm applications</a>.</p>
  
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Body: <p>I'm trying to learn how genetic algorithms can solve optimization problems. I have already learned how genetic algorithms can solve the knapsack, TSP and set cover problems. I'm looking for some other similar optimization problems, but I have not found any.</p>
  <p>Would you please mention some other famous optimization problems that can be solved by using genetic algorithms?</p>
  
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Comments.Text: If the answer below answers your question (and I think it should, if not, please, let me know why not), you should accept it by clicking the check symbol next to it. Take a look at https://ai.stackexchange.com/help/someone-answers.
Comments.UserDisplayName: nbro
Tags: <genetic-algorithms><optimization><applications><evolutionary-algorithms>
Title: What are examples of optimization problems that can be solved using genetic algorithms?
UserDisplayName: Pablo
ThreadText: # What are examples of optimization problems that can be solved using genetic algorithms?
  
  (Asked by: username_0 on 2019-10-05)
  
  I'm trying to learn how genetic algorithms can solve optimization problems. I have already learned how genetic algorithms can solve the knapsack, TSP and set cover problems. I'm looking for some other similar optimization problems, but I have not found any.
  
  Would you please mention some other famous optimization problems that can be solved by using genetic algorithms?
  
  **Tags:** genetic-algorithms, optimization, applications, evolutionary-algorithms
  
  > **Comments:**
  > **username_1**: If the answer below answers your question (and I think it should, if not, please, let me know why not), you should accept it by clicking the check symbol next to it. Take a look at https://ai.stackexchange.com/help/someone-answers.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-10-05. Score: 1
  
  There are numerous problems that can be solved with genetic algorithms or, more generally, with evolutionary algorithms (which includes also genetic programming and evolutionary strategies), even though they may not necessarily be the most efficient approach.
  
  Here are a few examples.
  
  * Evolution of the topology of neural networks. This is called [neuroevolution](https://en.wikipedia.org/wiki/Neuroevolution).
  * Automatic test case generation (in particular, for self-driving cars). [AsFault](https://www.researchgate.net/profile/Alessio_Gambi/publication/335362266_AsFault_Testing_Self-Driving_Car_Software_Using_Search-Based_Procedural_Content_Generation/links/5d70bd4792851cacdb21a956/AsFault-Testing-Self-Driving-Car-Software-Using-Search-Based-Procedural-Content-Generation.pdf) is one specific example.
  * Design of novel quantum computing algorithms. Specifically, genetic programming has been used to solve this problem (see [this reference](https://www.researchgate.net/publication/244428002_Genetic_Programming_for_Quantum_Computers) for more details).
  * As an alternative to reinforcement learning algorithms to solve RL problems. Specifically, evolution strategies have been successfully used in this case (see [this](https://openai.com/blog/evolution-strategies/)).
  
  There is a Wikipedia article that lists many other applications of genetic algorithms: [List of genetic algorithm applications](https://en.wikipedia.org/wiki/List_of_genetic_algorithm_applications).
  
  
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