Natee Panagant

TL;DR: The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.

TL;DR: A new self-adaptive meta-heuristic based on decomposition is specifically developed for this many-objective optimisation problem for an unmanned aerial vehicle (UAV) posed with 6 objective functions: take-off gross weight, drag coefficient, take off distance, power required, lift coefficient and endurance subject to aircraft performance and stability constraints.

TL;DR: The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm that is aimed at enhancement of the convergence rate of the original Henry gassolubility optimizer for solving real-life engineering optimization problems.

TL;DR: The comparative performance of fourteen new and established multi-objective metaheuristics when solving truss optimisation problems are investigated to provide new insights to the pros and cons of evolutionary multi- objective optimisation algorithms when addressing multiple, often conflicting objective in truss Optimisation.

TL;DR: The proposed algorithm, called fully stressed design–grey wolf–adaptive differential evolution (FSD-GWADE), is demonstrated to tackle a variety of truss optimization problems that have mixed continuous/discrete design variables.