🧑‍💻: Advanced Genetic Algorithm for Knapsack Problem

[HARSHIDS-4]

Title

The current genetic algorithm for the knapsack problem uses basic single-point crossover, fixed mutation, and zero-fitness penalty for overweight solutions. This leads to slow convergence and suboptimal solutions. The enhancement aims to improve GA efficiency, solution quality, and population diversity.

Enhancement Aim

improve convergence speed and solution quality by using advanced GA techniques.
Preserve best solutions through elitism and maintain diversity.
Handle overweight solutions gracefully with penalization or repair mechanisms.
Introduce adaptive mutation, multi-point crossover, and tournament selection for better exploration.

Changes

Adaptive mutation and multi-point crossover
Fitness penalization instead of zeroing
Elitism to preserve top individuals
Tournament selection for robust parent choice
Diversity maintenance to avoid stagnation
Optional gene repair for overweight solutions

Screenshots 📷

No response

Guidelines

• I have read the guidelines
• I have the link to my latest merged PR

Full Name

Harshi Gupta

Participant Role

GSSOC
HACKTOBERFEST

[github-actions]

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[github-actions]

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