Optimal Foraging Algorithm

OFA, inspired by the animal Behavioral Ecology Theory—Optimal Foraging Theory, has been developed.

An optimization algorithm, inspired by the animal Behavioral Ecology Theory—Optimal Foraging Theory, named the Optimal Foraging Algorithm (OFA) has been developed. As a new stochastic search algorithm, OFA is used to solve the global optimization problems following the animal foraging behavior. During foraging, animals know how to find the best pitch with abundant prey; in establishing OFA, the basic operator of OFA was constructed following this foraging strategy. During foraging, an individual of the foraging swarms obtained more opportunities to capture prey through recruitment; in OFA the recruitment was adopted to ensure the algorithm has a higher chance to receive the optimal solution. Meanwhile, the precise model of prey choices proposed by Krebs et al. was modified and adopted to establish the optimal solution choosing strategy of OFA.
More detail information can be found in the following reference.
Zhu, Guang-Yu, and Zhang, Wei-Bo. "Optimal foraging algorithm for global optimization." Applied Soft Computing 51 (2017): 294-313.