This paper presented an improved self‐adaptive particle swarm optimization (IDPSO)
algorithm with detection function to solve multimodal function optimization problems. To …

Aiming at the shortcomings of particle swarm optimization (PSO) algorithm, which is easy to
fall into local optimum and low precision during iteration, this paper proposes a self …

This chapter presents some of the recent modified variants of Particle Swarm Optimization
(PSO). The main focus is on the design and implementation of the modified PSO based on …

Many optimization problems in reality have become more and more complex, which promote
the research on the improvement of different optimization algorithms. The particle swarm …

The particle swarm optimizer (PSO) is a population-based optimization technique that can
be applied to a wide range of problems. This paper presents a variation on the traditional …

Particle swarm optimization (PSO) is one of the popular nature-inspired metaheuristic
algorithms. It has been used in different applications. The convergence analysis is among …

Particle swarm optimization (PSO) is one of the popular nature-inspired metaheuristic
algorithms. It has been used in different applications. The convergence analysis is among …

Initialization of the population in Evolutionary Computation algorithms is an issue of ongoing
research. Proper initialization may help the algorithm to explore the search space more …

Global optimization is a hot topic of applied mathematics and numerical analysis that deals
with the optimization of a function or a set of functions. In this paper we proposed a hybrid …

Optimization is a mathematical technique that concerns the finding of maxima or minima of
functions within some feasible region. A diversity of optimization techniques fight for the best …