Abstract
A new swarm intelligence optimization technique is proposed, called Artificial Coronary Circulation System (ACCS). This optimization method simulates the coronary arteries (veins) growth on human heart. In this algorithm, each capillary is considered as a candidate solution. This algorithm starts with a random initial population of candidate solutions, and by using Coronary Growth Factor (CGF) evaluates the solutions. In each run the best candidate solution is selected as the main coronary vessel (artery or vein) and the other capillaries are considered as searchers of the search space. Then the heart decides other candidates to move toward/away from the main coronary vessels and searches for the optimal solution by using the heart memory. Finally, application of the proposed algorithm is demonstrated using some benchmark functions and some mechanical problems, confirming the potential and capability of the new algorithm.
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