The success of the Particle Swarm Optimization (PSO) algorithm as a single-objective
optimizer (mainly when dealing with continuous search spaces) has motivated researchers …

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 …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

Many areas in power systems require solving one or more nonlinear optimization problems.
While analytical methods might suffer from slow convergence and the curse of …

Traditional multiobjective evolutionary algorithms (MOEAs) consider multiple objectives as a
whole when solving multiobjective optimization problems (MOPs). However, this …

Environmental problems, especially climate change, have become a serious global issue
waiting for people to solve. In the construction industry, the concept of sustainable building is …

In this paper, we present a generic method/model for multi-objective design optimization of
laminated composite components, based on Vector Evaluated Artificial Bee Colony …

A novel parallel approach to run standard particle swarm optimization (SPSO) on Graphic
Processing Unit (GPU) is presented in this paper. By using the general-purpose computing …

In this paper, three new particle swarm optimization (PSO) algorithms are compared with the
state of the art PSO algorithms for the optimal steady-state performance of power systems …

We present a new, generic method/model for multi-objective design optimization of
laminated composite components using a novel multi-objective optimization algorithm …