Abstract

Artificial Algae Algorithm (AAA) is an optimization algorithm that takes advantage of the swarm and evolutionary models. AAA consists of three phases, which are helical movement, reproduction, and adaptation. Helical movement is a three-dimensional motion which is highly influential in the convergence rate and diversity of solutions. Optimization of helical movement aims to increase the rate of convergence by moving the algae to the best colony in the population. Best colony in population is the closest to the best light source (the target solution), so that the movement is called Best Light Movement (BLM). AAA with movement toward the best light source (AAA-BLM) is tested and implemented in the case of pressure vessel design optimization. The test results indicate that the execution time of AAA-BLM increases 1,103 times faster than AAA. The increase in speed is caused by the tournament selection of AAA which is performed before the helical movement, while the AAA-BLM is conducted if a solution after the movement is not better than previous one. In the best condition, AAA-BLM finds a solution 4,5921 times faster than AAA. In the worst condition, AAA-BLM get stuck in local optima due to helical movement is too focused on the global best which may not be the global optima.

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