The slime mould algorithm (SMA) is a population-based optimization algorithm that mimics
the foraging behavior of slime moulds with a simple structure and few hyperparameters …

Multi-modal multi-objective optimization problem (MMOPs) has attracted more and more
attention in evolutionary computing recently. It is not easy to solve these problems using the …

Practical optimization problems often involve a large number of variables, and solving them
in a reasonable amount of time becomes a challenge. Competitive swarm optimizer (CSO) is …

In this paper, a parameter adaptation-based ant colony optimization (ACO) algorithm based
on particle swarm optimization (PSO) algorithm with the global optimization ability, fuzzy …

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

In order to effectively schedule railway train delay, an adaptive cooperative co-evolutionary
differential evolution with dynamic hybrid mechanism of the quantum evolutionary algorithm …

Particle swarm optimization (PSO) algorithm has a potential to solve route planning problem
for unmanned aerial vehicle (UAV). However, the traditional PSO algorithm is easy to fall …

With the development of cities, urban congestion is nearly an unavoidable problem for
almost every large-scale city. Road planning is an effective means to alleviate urban …

This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …

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