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The Bouquet Formation Optimization Algorithm (BFOA) is a nature-inspired optimization technique that simulates the arrangement of flowers into a bouquet, mimicking natural selection and interaction among flowers. In BFOA, each solution is represented as a flower, and the optimization process involves two main mechanisms:
- Pollination: Flowers interact and share characteristics, allowing better solutions to influence new flower formations, which helps explore the solution space effectively.
- Mutation: A portion of flowers undergo random changes to maintain diversity in the population, preventing premature convergence on suboptimal solutions.
The algorithm iteratively evaluates the fitness of each flower (solution) based on a predefined objective function, aiming to find the optimal arrangement (solution) over a specified number of iterations. BFOA is applicable to various optimization problems, including engineering design, scheduling, and resource allocation.
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