混合萤火虫与遗传算法解决0-1背包难题
Hybrid Firefly-Genetic Algorithm for Single and Multi-dimensional 0-1 Knapsack Problems
- 融合萤火虫与遗传算法优势，提升搜索能力
- 在0-1背包问题上精度更高，计算更快
- 适合工程设计与组合优化场景
本文针对萤火虫算法（FA）和遗传算法（GA）在约束优化问题中的表现下降问题，提出一种混合FAGA算法。该算法结合两者优势，用于求解无约束测试函数及含约束的工程设计问题与组合优化问题，如0-1背包问题。实验表明，相比传统优化算法，该方法在解的精度和计算效率方面均有提升，有效应对复杂优化挑战。
原文摘要 · Abstract (English)
This paper addresses the challenges faced by algorithms, such as the Firefly Algorithm (FA) and the Genetic Algorithm (GA), in constrained optimization problems. While both algorithms perform well for unconstrained problems, their effectiveness diminishes when constraints are introduced due to limitations in exploration, exploitation, and constraint handling. To overcome these challenges, a hybrid FAGA algorithm is proposed, combining the strengths of both algorithms. The hybrid algorithm is validated by solving unconstrained benchmark functions and constrained optimization problems, including design engineering problems and combinatorial problems such as the 0-1 Knapsack Problem. The proposed algorithm delivers improved solution accuracy and computational efficiency compared to conventional optimization algorithm. This paper outlines the development and structure of the hybrid algorithm and demonstrates its effectiveness in handling complex optimization problems.
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