Abstract The “No Free Lunch” theorem states that, averaged over all optimization problems,
without re-sampling, all optimization algorithms perform equally well. Optimization, search …

Particle swarm optimization (PSO) is a population-based stochastic search technique for
solving optimization problems over continuous space, which has been proven to be efficient …

To date, a large number of optimization algorithms have been presented for Autonomous
Underwater Vehicle (AUV) path planning. However, little effort has been devoted to compare …

A more efficient optimization algorithm has always been the pursuit of researchers, but the
performance of the current optimization algorithm in some complex test functions is not …

In recent years, the Particle Swarm Optimization has rapidly gained increasing popularity
and many variants and hybrid approaches have been proposed to improve it. In this paper …

The tower crane layout (TCL) problem, a typical construction site layout (CSL) problem, is
currently used in a wide range of construction projects and site conditions. The tower crane …

The successful handling of numerous real–world complex problems has increased the
popularity of nature–inspired intelligent (NII) algorithms and techniques. Their successful …

In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization
(PSO) are applied to the problem of damage detection using frequencies and mode shapes …

Enhancing reliability in complex systems often leads to allocating redundant elements and
identifying the system configuration by connecting various stages. Most of the redundancy …

The passage aims at solving the problems resulted from the optimized process of Particle
Swarm Optimization (PSO), which might reduce the population diversity, cause the algorithm …