Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …

Most of the complex research problems can be formulated as optimization problems.
Emergence of big data technologies have also commenced the generation of complex …

Given the significant recent advances in added layer manufacturing and materials
engineering, new types of materials or new material micro-structures are becoming …

Particle swarm optimization (PSO), like other population-based meta-heuristics, is
intrinsically parallel and can be effectively implemented on Graphics Processing Units …

Abstract A Supervised Parallel Optimisation (SPO) is presented. The proposed framework
couples different optimisation algorithms to solve single-objective optimisation problems …

To improve the marketability of novel microreactor designs, there is a need for automated
and optimal control of these reactors. This paper presents a methodology for performing …

This work presents a Particle Swarm Optimization (PSO) approach for non-periodic
preventive maintenance scheduling optimization. The probabilistic model, which is focused …

Due to the great complexity and the nonlinear and dynamic characteristics of joint
optimization operations in inter-basin water transfer-supply systems (IBWTS), rational …

A parallel master–slave model of the recently proposed cooperative micro-particle swarm
optimization approach is introduced. The algorithm is based on the decomposition of the …