Most real-world applications can be formulated as optimization problems, which commonly
suffer from being trapped into the local optima. In this paper, we make full use of the global …

As an intelligent algorithm inspired by the foraging behavior in nature, particle swarm
optimization (PSO) is famous for its few parameters, easy to implement and higher …

Particle swarm optimization (PSO) has received increasing interest from the optimization
community due to its simplicity in implementation and its inexpensive computational …

Particle swarm optimization (PSO) has demonstrated a promising performance for solving
challenging optimization problems, but its performance in solving large-scale optimization …

As a recently developed optimization method inspired by far-from-equilibrium dynamics of
self-organized criticality, extremal optimization (EO) has been successfully applied to a …

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 …

It is proposed to improve the study of particle optimization and its application in order to
solve the problem of inefficiency and lack of local optimization skills in the use of particle …

Large-scale optimization is a challenging problem because it involves a large number of
decision variables. In this paper, a simple but effective method, called hierarchical sorting …

Recently, a local-search heuristic algorithm called Extremal Optimization (EO) has been
successfully applied in some combinatorial optimization problems. However, there are only …

A comprehensive learning particle swarm optimizer (CLPSO) embedded with local search
(LS) is proposed to pursue higher optimization performance by taking the advantages of …