This paper presents a new Hybrid Particle Swarm optimization with Time Varying Acceleration Coefficients (HPSOTVAC) and Bacteria Foraging Algorithm (BFA) namely (PSOTVAC/BFA) base fuzzy stochastic long term approach for determining optimum location and size of Distributed Energy Resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load...

here are number of successful image quality metrics that rely on the structural information in an image in order to assess its perceptual quality. It is a challenging task to extract the structural information that is perceptually meaningful to the visual system. The current research is motivated by the observation that there is no single metric that provides the best performance scores in all ...

In this paper, Stochastic Economic Load Dispatch problem with Multiple Fuels is solved using Pareto distribution with local convex optimization by bacterial foraging approach. Bacterial foraging optimization is swarmed intelligence technique used to solve the problem of the power system. The algorithm is based on the group foraging behavior of Escherichia coli (E-coli) bacteria present in the h...

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimizat...

This Chapter summarizes some of the well known stigmergic computational techniques inspired by nature, mainly for optimization problems developed by mimicking social insects’ behavior. Some facts about social insects namely ants, bees and termites are presented with an emphasis on how they could interact and self organize for solving real world problems. We focused on ant colony optimization al...