Optimal Foraging Algorithm with Dynamic Parameter for Solving 0–1 Knapsack Problem

The optimal foraging algorithm is a swarm intelligence algorithm based on the foraging behavior of animal groups. This paper proposes an optimized foraging algorithm with dynamic parameters to improve the search performance by changing the scaling factor to increase the convergence accuracy and convergence speed. Testing on 10 benchmark functions showed that the modified optimization foraging algorithm outperforms the comparison algorithms in terms of convergence accuracy and convergence speed. The modified optimal foraging algorithm is used to solve the 0–1 knapsack problem, and the experimental results show that the modified optimal foraging algorithm can achieve better results.