Multi-strategy adaptive particle swarm optimization for numerical optimization

Dynamic mentoring and self-regulation based particle swarm optimization algorithm for solving complex real-world optimization problems

“…This novel strategy updates a given particle's velocity using all other particles' personal best information. Further refinements include the usage of personal best of neighbouring particles [47,31], distance and fitness information [51,61], multi-layer swarms [36,62] and multi-swarm strategies [7,69]. The refinements and modifications of the PSO algorithm using different learning strategies and hybridization have successfully provided better solutions to the complex optimization problems.…”

A novel parallel multi-swarm algorithm based on comprehensive learning particle swarm optimization

“…These subswarms optimize cooperatively the different parts of a problem and the solution vector is composed of the results of the subswarms. In Tang et al (2015), a multi-strategy adaptive particle swarm optimization (MAPSO) was proposed to search the global optimum in the entire search space with a very fast convergence speed. MAPSO changes dynamically the inertia weight according to the status of particles and introduces an elitist learning strategy to enhance the diversity of population.…”

A Hybrid Bacterial Foraging Optimization Algorithm and a Radial Basic Function Network for Image Classification

“…In order to explore separately the local and global search proprieties of BFOA, researchers hybridized it with other algorithms, applied it to several real world problems and proved its effectiveness over many works, e.g., mathematical modeling for solving simultaneous equation problems [19], solving scheduling problems [12], mechanical problems [2], solar PV modeling [20], and numerical optimization [1]. More hybridization is observed in [18,21].…”

“…Independently of classical optimization methods, like the gradient-based and the quasi-Newton methods [1], there are several widespread and well-established methods based on heuristic population as artificial immune system (AIS), ant colony algorithm (AC), and artificial neural network (ANN) [2].…”