Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …

Differential evolution (DE) algorithm is prone to premature convergence and local
optimization in solving complex optimization problems. In order to solve these problems, the …

Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …

The selection of the mutation strategy for differential evolution (DE) algorithm plays an
important role in the optimization performance, such as exploration ability, convergence …

In this paper, a novel competitive swarm optimizer (CSO) for large scale optimization is
proposed. The algorithm is fundamentally inspired by the particle swarm optimization but is …

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter
optimization algorithms in current use. DE operates through similar computational steps as …

Differential evolution (DE) is an efficient and powerful population-based stochastic search
technique for solving optimization problems over continuous space, which has been widely …

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that
significantly reduces the efficiency of the overall system. Under this condition, the PV system …

In nature, almost every organism ages and has a limited lifespan. Aging has been explored
by biologists to be an important mechanism for maintaining diversity. In a social animal …