Analysis of various algorithms for optimizing the wave energy converters associated with a sloped wall-type breakwater

Unlocking the Ocean 6G: A Review of Path-Planning Techniques for Maritime Data Harvesting Assisted by Autonomous Marine Vehicles

“…As a result, conventional point-to-point path-planning methodologies, typified by heuristic paradigms such as A* [52,53], D* [54,55], and theta* [56][57][58], as well as samplingbased techniques including Rapidly-exploring Random Trees (RRT*) [59][60][61] and Probabilistic Roadmaps (PRMs) [62,63], show a relative scarcity of application within this field. Contrastingly, meta-heuristic techniques, such as genetic algorithms (GA) [64,65], ant colony optimization (ACO) [66,67], particle swarm optimization (PSO) [68,69], simulated annealing (SA) [70,71], alongside AI-driven approaches exemplified by Q-learning and deep reinforcement learning, exhibit a remarkable ability to accommodate the intricate nature of the problem formulation. Notably, these methodologies not only present a capacity to optimize diverse sets of objective functions but also show an adeptness at navigating the complex constraints.…”

Optimization Analysis of the Shape and Position of a Submerged Breakwater for Improving Floating Body Stability

“…Gandomi et al (2023) analyzed the reflection and transmission coefficients of by permeable breakwaters using the conditional value-at-risk method (CvaR) based on the multilayer perceptron neural network and second-generation nondominated sorting genetic algorithm (NSGA-II). Jeong and Koo (2023) conducted an optimization analysis of the power output of wave energy converters using the three-dimensional frequency-domain boundary element method (FD-BEM) based on the potential flow theory. They compared the optimization analysis results for genetic algorithms, simulated annealing, particle swarm optimization (PSO), and advanced PSO (Chen et al, 2018), and described the superiority of advanced PSO.…”

“…To the best of our knowledge, the development of a linked analysis framework of NWT and an optimization algorithm that can analyze the 2D hydrodynamic problems considering various sea bottoms was attempted for the first time. As a metaheuristic algorithm, the advanced PSO proposed by Chen et al, (2018) and demonstrated superiority by Jeong and Koo (2023) was used in this study. The optimization analysis is performed by calling FD-BEM for each generation, conducting a numerical analysis of the design variables of each particle, and updating the design variables using the collected results.…”