Particle swarm optimization algorithm for a model of optimally scheduling web advertising resources
Dingwei Wang · Kongzhi yu juece · 2004
A model of scheduling web advertising resources for maximizing advertising effect function is proposed, according to the properties of web advertising. A quadratic punishing item that separates the advertising impressions is added to the Langheinrich linear model, in order to better exert advertising efficacy with the optimized solution. An improved particle swarm optimization (PSO) algorithm is designed to handle the constraint efficiently, (considered) the properties of PSO algorithm and constraint of models. Simulation result shows the validity of this (algorithm.)