Machine learning develops rapidly, which has made many theoretical breakthroughs and is
widely applied in various fields. Optimization, as an important part of machine learning, has …

The set-based particle swarm optimisation algorithm is a swarm-based meta-heuristic that
has gained popularity in recent years. In contrast to the original particle swarm optimisation …

The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong
in 1994 and since then many CCEAs have been proposed and successfully applied to …

This article proposes a competitive divide-and-conquer algorithm for solving large-scale
black-box optimization problems for which there are thousands of decision variables and the …

In the photonic design problem, a scientist or engineer chooses the physical parameters of a
device to best match some desired device behavior. Many instances of the photonic design …

Quantum technologies exploit entanglement to enhance various tasks beyond their classical
limits including computation, communication and measurements. Quantum metrology aims …

Evolution strategies are a class of evolutionary algorithms for black-box optimization and
achieve state-of-the-art performance on many benchmarks and real-world applications …

This article presents a new method to solve the inverse kinematics problem of hyper-
redundant and soft manipulators. From an engineering perspective, this kind of robots are …

Estimation of distribution algorithm (EDA) is a stochastic optimization algorithm based on
probability distribution model and has been widely applied in global optimization. However …

Solar cells are one of the renewable energy sources that have been widely used. The
parameters extraction plays an important role in the speed and accuracy of models …