Browse Proceedings

This paper introduces a novel method named DEGL (Differential Evolution with global and local neighborhoods) regarding the design of two channel quadrature mirror filter with linear phase characteristics. To match the ideal system response ...

In the present work we propose a modified variant of Differential Evolution (DE) algorithm named MDE. MDE differs from the basic DE in the manner in which the base vector is generated. While in simple/basic DE, base vector is usually randomly selected ...

In this paper we propose a self adaptive cluster based Differential Evolution (DE) algorithm to solve the Dynamic Optimization Problems (DOPs). We have enhanced the classical DE to perform better in dynamic environments by a powerful clustering ...

We propose an informative Differential Evolution (DE) algorithm where the information gained by the individuals of a cluster will be exchanged after a certain number of iterations called refreshing gap. The DE is empowered with a clustering technique to ...

Image edge enhancement is the art of enhancing the edge of significant objects in an image. The proposed work uses the concept of hybrid filters for edge enhancement whose optimal sequence is to be found by differential evolution. Its unbiased ...

This paper investigates the performance of Differential Evolution (DE) in solving a Flexible Assembly Line (FAL) scheduling problem. Using a mathematical model developed in literature, the DE algorithm is implemented with the objectives of minimizing ...

Image entropy thresholding is one of the most widely used technique for multilevel thresholding. The endeavor of this paper is to focus on obtaining the optimal threshold points. Several meta-heuristics are being applied in literatures over the decade, ...

In this paper, differential evolution (DE) optimization algorithm is applied to design robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and DE is employed to search for optimal ...

This paper presents a new adaptive differential evolution technique based on logistic map for optimal distribution placement and sizing. The parameters of differential evolution that need to be selected by the user are the key factors for successful ...

An Improved Multiobjective Generalized Differential Evolution (I- GDE3) approach is proposed in this paper. For maintaining good diversity, the concepts of Simulated Binary Crossover (SBX) based recombination and Dynamic Crowding Distance (DCD) are ...

This paper presents an enhanced differential evolution technique to solve the optimal coordination of directional overcurrent relays in a power system. The most vital task when installing directional relays on the system is selecting suitable current ...

Dynamic thinning is a process by which the total number of active elements in an antenna array is reduced under real time conditions without causing major degradation in system's performances. This paper suggests a technique by which a thinned antenna ...

The design of antenna arrays aims at minimizing side-lobe levels far as practicable. So a major concern of designer is to optimize the side lobes to increase directivity, gain, and efficiency. Invasive Weed Optimization (IWO) is a recently developed, ...

The optimal power flow (OPF) has been commonly used as an efficient tool in the power system planning and operation for many years. OPF is an important tool in modern Energy Management System (EMS). It plays an important role in maintaining the economy ...

Many real-world optimization problems are dynamic in nature. In order to deal with these Dynamic Optimization Problems (DOPs), an optimization algorithm must be able to continuously locate the optima in the constantly changing environment. In this paper,...

Memetic Algorithm is a metaheuristic search method. It is based on both the natural evolution and individual learning by transmitting unit of information among them. In the present paper, Genetic Algorithm due to its good exploration capability is used ...

An Unified Power Flow Controller (UPFC) is a typical Flexible AC Transmission System (FACTS) device playing a vital role as a stability aid for large transient disturbances in an interconnected power system. This paper deals with the design of Feedback ...

In distribution system, the size and location of shunt capacitors for peak power loss and energy loss reduction plays a vital role. This paper proposes a new method, Nelder-Mead particle swarm optimization (NM-PSO) for the optimal capacitor placement ...

This paper focuses on unit sizing of stand-alone hybrid energy system using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) and comparative performance study of these two meta-heuristic techniques on hybrid energy system. The hybrid system ...

A pixel-level multi-focus image fusion scheme using Independent Component Analysis (ICA) and Particle Swarm Optimization (PSO) is proposed in this paper. The novelty in this work is optimization of ICA bases using PSO and its application to multi-focus ...

This paper presents a Hybrid Genetic Algorithm (HGA) Particle Swarm Optimization (PSO) approach to solve Economic Emission Optimal Power Flow problem. The proposed approach optimizes two conflicting objective functions namely, fuel cost minimization and ...

This paper addresses short-term scheduling of hydrothermal systems by using Particle Swarm Optimization (PSO) algorithm. Particle Swarm Optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal power system. ...

Grid computing infrastructure emerged as a next generation of high performance computing by providing availability of vast heterogenous resources. In the dynamic envirnment of grid, a schedling decision is still challenging. In this paper, we present ...

This article presents an efficient optimization approach to solve constrained Economic Load Dispatch (ELD) problem using a ‘Lbest-Particle Swarm Optimization with Dynamically Varying Sub-swarms' (LPSO-DVS). The proposed method is found to give optimal ...

A particle swarm optimization model for tracking multiple peaks over a multimodal fitness landscape is described here. Multimodal optimization amounts to finding multiple global and local optima (as opposed to a single solution) of a function, so that ...

Constrained function optimization using particle swarm optimization (PSO) with polynomial mutation is proposed in this work. In this method non-stationary penalty function approach is adopted and polynomial mutation is performed on global best solution ...

This paper investigates a hybrid fusion methodology by incorporating ranks and decisions of a user in a multimodal biometric system using PSO. Each of the biometric modalities is first used to rank the users. The individual ranks are then integrated to ...

Clustering can be visualized as a grouping problem as it consists of identifying finite set of groups in a dataset. Grouping genetic algorithms are specially designed to handle grouping problems. As the clustering criteria such as minimizing the with-in ...

Software engineering cost models and estimation techniques are used for number of purposes. These include budgeting, tradeoff and risk analysis, project planning and control, software improvement and investment analysis. The proposed work uses neural ...

Standard Genetic Algorithms (SGAs) is modeled as a simple set of fixed size individuals and each individual has no gender. The idea is based on non-random mating and important role of religious in the organization of societies. Essential concepts of ...