Masterpiece Optimization Algorithm: A New Method for Solving Engineering Problems - Mohammad Reza Ghasemi; Nader Haji Aghajanpour; Hamed Ghohani Arab (Journal of Soft Computing in Civil Engineering)
The "Masterpiece Optimization Algorithm (MOA)" is introduced as a new nature-inspired meta-heuristic optimization method that mimics the masterpiece of Japanese Male Puffer Fishes (MPFs) that succeed in mating. Actually, the nest prepared by the MPFs for spawning is known as the masterpiece. Due to the importance of seabed fine sand to fish reproduction, the proposed algorithm is based on movement and accumulation of seabed fine sand particles. In order to find a place with a sufficient amount of fine sand for spawning, the MPF starts a search on the seabed. It then constructs the nest so that fine sand covers the eggs. The location with the greatest quantity of fine sand is where the majority of egg protection occurs. In the algorithm, this point is considered the global optimum. Now, to handle this content, in the first iteration of the proposed algorithm, different points in the answer zone are introduced for the MPF. Then, the MPF selects a point for the nest location using the Evaluator Function (EF). In continuation of the first iteration, three steps are executed. The point acquired in the third step represents a local optimum. For the next iteration, this point is deemed the nest location, and the aforementioned three steps are also executed. This process is done iteratively during each iteration. The best point of the last iteration is the global optimum of the problem in the answer zone. The obtained solutions of the MOA were then compared with some available techniques in the literature.