Abstract
This paper presents a novel efficient meta-heuristic optimization algorithm called Colliding Bodies Optimization (CBO). This algorithm is based on one-dimensional collisions between bodies, with each agent solution being considered as an object or body with mass. After a collision of two moving bodies having specified masses and velocities, these bodies are separated with new velocities. This collision causes the agents to move toward better positions in the search space. CBO utilizes simple formulation to find minimum or maximum of functions and does not depend on any internal parameter. Numerical results show that CBO is competitive with other meta-heuristics.
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