Memetic algorithms are used for optimization in cases where the objective function is costly and the population-based nature of the search is evaluated by the memetic algorithm. In rule-based systems, a significant number of generations are required to find the optimal value of the objective function. One of the methods of generating the rule of the learning classifier system. The function of the learning classifier systems is based on the genetic algorithm, it is not possible to search and save the previous steps in order to find a better solution to the problem. In this article, the memetic algorithm is used to improve and optimize the learner classification system. In the proposed algorithm, the memetic algorithm is used to create a population to improve the learning classifier system in the state space. The efficiency of the proposed method is demonstrated using the implementation. The results show that the proposed hybrid method of replacing the memetic algorithm in the learning classifier system can significantly speed up the hybrid system and improve the quality.
dehghanimahmoudabadi, M., & nabavizadeh, N. (2024). Improving the learning classifier system with the basic memetic algorithm to solve the problem based on the law. Engineering Management and Soft Computing, (), -. doi: 10.22091/jemsc.2023.8700.1166
MLA
mohammadreza dehghanimahmoudabadi; nagmalsadat nabavizadeh. "Improving the learning classifier system with the basic memetic algorithm to solve the problem based on the law". Engineering Management and Soft Computing, , , 2024, -. doi: 10.22091/jemsc.2023.8700.1166
HARVARD
dehghanimahmoudabadi, M., nabavizadeh, N. (2024). 'Improving the learning classifier system with the basic memetic algorithm to solve the problem based on the law', Engineering Management and Soft Computing, (), pp. -. doi: 10.22091/jemsc.2023.8700.1166
VANCOUVER
dehghanimahmoudabadi, M., nabavizadeh, N. Improving the learning classifier system with the basic memetic algorithm to solve the problem based on the law. Engineering Management and Soft Computing, 2024; (): -. doi: 10.22091/jemsc.2023.8700.1166
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