Lice-inspired optimization algorithm for numerical optimization and engineering design
Neda Matin, Mina Zolfy Lighvan, Leili Farzinvash · International Journal of General Systems · 2025
This paper introduces the Lice Optimization Algorithm (LOA), a novel metaheuristic inspired by the life cycle of lice, designed to address continuous optimization problems. The algorithm simulates key stages of lice development, including growth, ovipositional, and aging processes. A chaos-based approach is integrated during the growth phase to enhance exploration and avoid local optima. The selection of egg locations, along with parental and ovipositional selection techniques, facilitates the transfer of desirable traits across generations. Additionally, a lifespan-based selection operator regulates population diversity and resilience. The performance of LOA was extensively evaluated using 29 benchmark functions, 10 CEC2019 functions, 12 CEC2022 functions, and eight real-world engineering problems. Evaluation metrics included convergence speed, stability, execution time, and scalability. Statistical analyses, including the Friedman and Wilcoxon tests, confirm the robustness of the results. LOA demonstrated superior performance compared to 15 other optimization methods, highlighting its effectiveness in solving continuous optimization challenges.