Abstract Particle Swarm Optimization (PSO), in its present form, has been in existence for
roughly a decade, with formative research in related domains (such as social modelling …

Particle swarm optimization (PSO) is predominately used to find solutions for continuous
optimization problems. As the operators of PSO are originally designed in an n-dimensional …

This paper presents the novel application of a collaborative population-based meta-heuristic
technique called Particle Swarm Optimization (PSO) to the scheduling of home care …

Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters
and is computationally simple and easy to implement, it is not a globally convergent …

Particle swarm optimisation (PSO) has been enormously successful. Within little more than a
decade hundreds of papers have reported successful applications of PSO. In fact, there are …

Most swarm intelligence algorithms were devised for continuous optimization problems.
However, they have been adapted for discrete optimization as well with applications in …

Recently, various multiobjective particle swarm optimization (MOPSO) algorithms have been
developed to efficiently and effectively solve multiobjective optimization problems. How ever …

Particle swarm optimization (PSO) is one of the most popular population-based stochastic
algorithms for solving complex optimization problems. While PSO is simple and effective, it is …

Abstract Model-based decision-making in oilfield development often involves hundreds of
computationally demanding reservoir simulation runs. In particular, well placement …

In this paper we present a multi-start particle swarm optimization algorithm for the global
optimization of a function subject to bound constraints. The procedure consists of three main …