A discrete binary version of the particle swarm algorithm

Abstract

The particle swarm algorithm adjusts the trajectories of a population of "particles" through a problem space on the basis of information about each particle's previous best performance and the best previous performance of its neighbors. Previous versions of the particle swarm have operated in continuous space, where trajectories are defined as changes in position on some number of dimensions. The present paper reports a reworking of the algorithm to operate on discrete binary variables. In the binary version, trajectories are changes in the probability that a coordinate will take on a zero or one value. Examples, applications, and issues are discussed.

Optimal Rectangular Microstrip Antenna with and without Air Gaps Design by Means of Particle Swarm Optimization and Vortex Search Algorithm

“…It has been developed on the behavior of the animal when they search for food sources. Even members of swarm has no information about food location, they have ability to find sources due to cognitive, social and exploratory policies of swarm [11]. Every member is assumed based on generally accepted expression as a particle.…”

Spectrum Allocation Based on an Improved Gravitational Search Algorithm

“…First, we introduce the evaluation criteria for algorithm performance. Second, we construct the environment for experiments and initialize parameters for algorithms (IGSA, GSA [19], PSO [23] and color sensitive graph coloring(CSGC) [24]). Third, we conduct experiments and analyze the experimental results.…”

Particle Swarm Optimization for Power Dispatch with Pumped Hydro

“…The proposed approach combines a binary version of the PSO technique with a mutation operation. Kennedy and Eberhart first introduced the concept of binary PSO and demonstrated that a binary PSO was successfully applied to solve a discrete binary problem (Kennedy & Eberhart, 1997). In this work, since all Taipower's pumped hydro units are designed for constant power pumping, novel binary encoding/decoding techniques are judiciously devised to model the discrete characteristic in pumping mode as well as the continuous characteristic in generating mode.…”