Multimodal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions
in a single simulation run has practical relevance to problem solving across many fields …

Various real-world applications can be classified as expensive multimodal optimization
problems. When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle …

This paper presents an overview of our most recent results concerning the Particle Swarm
Optimization (PSO) method. Techniques for the alleviation of local minima, and for detecting …

Many scientific, engineering and economic problems involve the optimisation of a set of
parameters. These problems include examples like minimising the losses in a power grid by …

This paper constitutes a first study of the Particle Swarm Optimization (PSO) method in
Multiobjective Optimization (MO) problems. The ability of PSO to detect Pareto Optimal …

The performance of the Particle Swarm Optimization method in coping with Constrained
Optimization problems is investigated in this contribution. In the adopted approach a non …

This paper presents approaches for effectively computing all global minimizers of an
objective function. The approaches include transformations of the objective function through …

Particle swarm optimization (PSO) has shown its fast search speed in many complicated
optimization and search problems. However, PSO could often easily fall into local optima …

The investigation of the performance of the particle swarm optimization (PSO) method in
integer programming problems, is the main theme of the present paper. Three variants of …

Particle swarm optimization is a stochastic population-based algorithm based on social
interaction of bird flocking or fish schooling. In this paper, a new adaptive inertia weight …