April 26, 2024

Research on Goal Planning Problem Based on Genetic Algorithm

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Analysis of genetic algorithm effectiveness in optimization, highlighting its capacity for complex problem-solving.

The genetic algorithm efficiently solves optimization problems, particularly in complex situations with multiple constraints.
Effective outcomes include finding optimal paths while minimizing length and adhering to time limits during problem solving.
Typical genetic algorithm processes such as selection, crossover, and mutation were utilized to enhance performance and adaptability of the algorithm. The study showcases the algorithm's potential for practical applications, emphasizing its role in facilitating effective optimization solutions.

Hao et al. (2024) studied this question.

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