The development and application of evolutionary algorithms (EAs) and other metaheuristics
for the optimisation of water resources systems has been an active research field for over …

Python has become the programming language of choice for research and industry projects
related to data science, machine learning, and deep learning. Since optimization is an …

Over the last three decades, a large number of evolutionary algorithms have been
developed for solving multi-objective optimization problems. However, there lacks an upto …

Previous studies have established that the folding, structure and function of membrane
proteins are influenced by their lipid environments,,,,,, and that lipids can bind to specific …

This paper investigates the use of reinforcement learning for the robust design of low-thrust
interplanetary trajectories in presence of severe uncertainties and disturbances, alternately …

Among the existing global optimization algorithms, Particle Swarm Optimization (PSO) is
one of the most effective methods for non-linear and complex high-dimensional problems …

Feature selection is a necessary critical stage in data mining process. There is always an
arm race to build frameworks and libraries that ease and automate this process. In this …

Given the depletion of metal resources and the potential leaching of toxic elements from
solid waste, secondary recovery of metal from solid waste is essential to achieve …

Nature-inspired algorithms are a very popular tool for solving optimization problems (Yang
2014),(Hassanien and Emary 2016). Numerous variants of nature-inspired algorithms have …

Abstract The three Laser Interferometer Space Antenna (LISA) spacecraft are going to be
placed in a triangular formation in an Earth-trailing or Earth-leading orbit. They will be …