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 …

Particle swarm optimization (PSO) algorithm is such a simple, easily understood and
realizable concept that it has been developing rapidly and has been applied widely since it …

A particle swarm optimization algorithm with crossover operation (PSOCO) is proposed. In
the proposed PSOCO, two different crossover operations are employed in order to breed …

Particle swarm optimization (PSO) has been in practice for more than 10 years now and has
gained wide popularity in various optimization tasks. In the context to single objective …

PARTICLE swarm optimization (PSO) is one of the evo-lutionary computation techniques. It
is a population-based search algorithm and is initialized with a population of random …

Particle swarm optimization (PSO) is a new evolutionary computation technique. Although
PSO algorithm possesses many attractive properties, the methods of selecting inertia weight …

This chapter covers the the inspiration, mathematical model, and main mechanisms of the
Particle Swarm Optimisation (PSO). The binary version of this algorithm (BPSO) is also …

In this paper, a hybrid particle swarm optimization algorithm (HPSOM) that uses the mutation
process to improve the standard particle swarm optimization (PSO) algorithm is presented …

Particle swarm optimization (PSO) has been widely applied in solving optimization problems
because of its simple execution with fast convergence and high solution quality as known …

In this paper, aim at the disadvantages of standard Particle Swarm Optimization algorithm
like being trapped easily into a local optimum, we improves the standard PSO and proposes …