Due to the increasing complexity of optimization problems, distributed differential evolution
(DDE) has become a promising approach for global optimization. However, similar to the …

In the last few decades, genetic algorithms (GAs) demonstrated to be an effective approach
for solving real-world optimization problems. However, it is known that, in presence of a …

Multimodal optimization aiming at locating multiple global optima at a time has received
extensive attention from researchers since it can afford multiple choices for decision-makers …

Various real-world problems can be attributed to constrained multiobjective optimization
problems (CMOPs). Although there are various solution methods, it is still very challenging …

Gravitational search algorithm is an effective population-based algorithm. It simulates the
law of gravity to implement the interaction among particles. Although it can effectively …

In this paper, we proposed a novel fitness-value-independent Differential Evolution to tackle
complex real-parameter single-objective optimization. There were three innovations in the …

Differential evolution (DE) is a simple and efficient global optimization algorithm. Benefitting
from its concise structure and strong search ability, DE has been widely used in various …

The main parameters that affect the performance of a differential evolution algorithm are the
scaling factor, crossover rate, and population size. To adaptively adjust the population …

Differential Evolution (DE) is one of the most effective approaches in Evolutionary
Computation to tackling complex black-box optimization, however, the overall performance …

Spherical search algorithm (SSA) calculates the spherical boundary and generates new
solutions on it by two sub-populations jointly. Many researches have shown that SSA is a …