Swarm

Abstract-In this paper an efficient hybrid optimization approach is used to solve the optimal power flow problem. In the proposed approach particle swarm optimization along with ant colony optimization is used for setting of control variables for optimal power flow problem. The proposed approach is tested and examined in standard IEEE 30 bus test system. The various objective functions involved are fuel cost minimization, voltage profile improvement and transmission loss reduction. This proposed

by considering advance payment and partial backlogging with interval valued inventory cost. In this model, the corresponding optimization problem with interval objective has been formulated and solved with the help of different variants of particle swarm optimization (PSO) technique and interval order relations. Due to interval valued inventory cost, the different variants of PSO algorithm have been developed by using interval arithmetic and interval order relations. Then the obtained best found

with certain values. These parameters include operation and maintenance coefficient, number of variables, and constraints such as boundaries of variables and battery, charge and discharge efficiency, maximum number of iteration, population size or swarm size, inertia weight and its damping ratio, personal and global learning coefficient, and velocity limits. Step 2: PSO is initialized with a group of random particles. Each particle has its own position, velocity, and best position called personal

section{Evolutionary Computation} Evolutionary Computation is a subfield of Artificial Intelligence. It is very well-known as its effective global search ability. These algorithms are inspired by biological mechanisms of evolution, social interactions and swarm intelligence. There are several distinguished characteristics of EC algorithms such as the use of a population and the ability of avoiding local optima. A common process of EC algorithms is as follows. Initially, the population are randomly scattered

Engineering and Information, Amirkabir University of Technology 1Pen.khaleghi@gmail.com 2R_k_moghaddam@mshdiau.ac.ir 3 Amir.e.musavi@gmail.com 4El.ghahremani@aut.ac.ir Abstract— This paper involves a novel application of the improved particle swarm optimization (IPSO) in an economic dispatch problem (EDP) that consists influence of valve-point loading, power balance, and generators constraints. This method is able to improve the best value of the cost function with a slight increase in the average

Hybrid Cuckoo ABC Algorithm for optimistic job scheduling in Heterogeneous Computing Systems Amit Chhabra1, Harwinder Kaur2 1 Guru Nanak Dev University, Amritsar Punjab, India Harwindersaini16@gmail.com, Amit.cse@gndu.ac.in Abstract Cloud Computing is now extremely popular because of its wide variety of Applications through internet. The particular service based approaches which are aware from the server selection through the cloud can easily progress toward the cost and performance of

A Hybrid Cuckoo Algorithm and Practice Swarm Optimization for Planning of Parking Lots in Distribution systems Mohamad Esmaili*, 1: Faculty of Engineering, Department of Electrical Engineering,Azad Shiraz University, Shiraz, Iran *Corresponding author. Tel +98-551-5824978; fax: +98-5007350826. E-mail addresses: mohamad709@gmail.com Abstract-Plug in Electric Vehicles (PEVs) have been proportionally innovated as a sufficient solution in smart grids in response to Green House Gases (GHGs)

methods have proved their excellence in giving better results by improving the steady state characteristics and performance indices [8]. Neha Kundariya, Jyoti Ohri in their research paper titled ‘Design of Intelligent PID Controller using Particle Swarm Optimization with different Performance Indices’ proposed a PSO based PID controller for controlling of DC shunt motor using different performance indices like Integral of Time multiplied by Absolute Error (ITAE), Integral of Absolute magnitude of

Chapter Three A Proposed Design of Intelligent Controller for Solar Tracking System 3.1 Introduction One of the most important methods used for obtaining the solution to analysis and design controller for sun tracking system is the computer simulation. All simulations are implemented using MATLAB R2013a and Proteus 7 Professional. 3.2 Sun Tracker Solar tracking system uses two DC motors to rotate the solar panel in two axes. The position of the sun is adjusted by using four LDR as

In previous chapters, the advantages and disadvantages of several modulation methods for multilevel converter have been summarized. In this chapter Fourier series and harmonic elimination theory is discussed briefly to derive the transcendental equations for the fundamental frequency switching method for multilevel inverter. In the second part of this chapter a new evolutionary technique Big Bang-Big Crunch optimization is used for solving the transcendental equations for the fundamental frequency