Advanced Intelligent Computing Theories and Applications

Volume 6215 of the series Lecture Notes in Computer Science pp 309-318

Parameter-Free Deterministic Global Search with Simplified Central Force Optimization

  • Richard A. FormatoAffiliated withCarnegie Mellon UniversityRegistered Patent Attorney & Consulting Engineer

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This note describes a simplified parameter-free implementation of Central Force Optimization for use in deterministic multidimensional search and optimization. The user supplies only the objective function to be maximized, nothing more. The algorithm’s performance is tested against a widely used suite of twenty three benchmark functions and compared to other state-of-the-art algorithms. CFO performs very well.


Central Force Optimization CFO Deterministic Algorithm Multidimensional Search and Optimization Parameter-Free Optimization Gravitational Kinematics Metaphor Metaheuristic