A new human-based metaheuristic algorithm for solving optimization problems based on preschool education

Area of Science:

• Computer Science
• Artificial Intelligence
• Optimization Algorithms

Background:

• The No Free Lunch theorem highlights the need for specialized optimization algorithms.
• Metaheuristic algorithms are crucial for solving complex computational problems.
• Existing algorithms may struggle with balancing exploration and exploitation effectively.

Purpose of the Study:

• Introduce a novel human-based metaheuristic algorithm, the Preschool Education Optimization Algorithm (PEOA).
• To address the limitations of current optimization techniques by drawing inspiration from preschool education.
• To evaluate the performance and efficacy of PEOA on a diverse set of benchmark and real-world problems.

Main Methods:

• PEOA is mathematically modeled based on three phases of preschool education: teacher's influence, guided knowledge development, and self-awareness.
• The algorithm's performance is assessed using 52 standard benchmark functions (unimodal, multimodal) and the CEC 2017 test suite.
• Comparative analysis involves PEOA against ten established metaheuristic algorithms and statistical testing (Wilcoxon signed-rank test).

Main Results:

• PEOA demonstrates a strong capability in balancing exploration and exploitation during the optimization process.
• The algorithm achieved superior performance compared to ten well-known metaheuristic algorithms across various benchmark functions.
• Statistical analysis confirmed the significant superiority of PEOA over competing methods, ranking it as the top optimizer.
• PEOA showed effectiveness in solving CEC 2011 test suite problems and four engineering design challenges.

Conclusions:

• The Preschool Education Optimization Algorithm (PEOA) is a highly effective and statistically superior metaheuristic for optimization problems.
• PEOA's unique design, inspired by educational processes, allows for efficient exploration-exploitation balance.
• The algorithm shows significant promise for real-world applications in engineering and other complex domains.