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Vellore, India

VIT University formerly called Vellore Engineering College is an Indian institute of higher education and a Deemed University under Section 3 of the UGC Act. Founded in 1984, as Vellore Engineering College, by Mr. G. Viswanathan, the institution offers 20 undergraduate, 34 postgraduate, 4 integrated and 4 research programs. The university and draws students from 50 countries as well as from every state in India. It has campuses both at Vellore and Chennai, Tamil Nadu, India Wikipedia.

Noel M.M.,Vellore Institute of Technology
Applied Soft Computing Journal | Year: 2012

Stochastic optimization algorithms like genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms perform global optimization but waste computational effort by doing a random search. On the other hand deterministic algorithms like gradient descent converge rapidly but may get stuck in local minima of multimodal functions. Thus, an approach that combines the strengths of stochastic and deterministic optimization schemes but avoids their weaknesses is of interest. This paper presents a new hybrid optimization algorithm that combines the PSO algorithm and gradient-based local search algorithms to achieve faster convergence and better accuracy of final solution without getting trapped in local minima. In the new gradient-based PSO algorithm, referred to as the GPSO algorithm, the PSO algorithm is used for global exploration and a gradient based scheme is used for accurate local exploration. The global minimum is located by a process of finding progressively better local minima. The GPSO algorithm avoids the use of inertial weights and constriction coefficients which can cause the PSO algorithm to converge to a local minimum if improperly chosen. The De Jong test suite of benchmark optimization problems was used to test the new algorithm and facilitate comparison with the classical PSO algorithm. The GPSO algorithm is compared to four different refinements of the PSO algorithm from the literature and shown to converge faster to a significantly more accurate final solution for a variety of benchmark test functions. © 2011 Elsevier B.V. All rights reserved. Source

Das N.,Vellore Institute of Technology
Clean - Soil, Air, Water | Year: 2012

The development of nuclear science and technology has led to the increase of nuclear wastes containing radionuclides to be released and disposed in the environment. Pollution caused by radionuclides is a serious problem throughout the world. To solve the problem, substantial research efforts have been directed worldwide to adopt sustainable technologies for the treatment of radionuclide containing wastes. Biosorption represents a technological innovation as well as a cost effective excellent remediation technology for cleaning up radionuclides from aqueous environment. A variety of biomaterials viz. algae, fungi, bacteria, plant biomass, etc. have been reported for radionuclide remediation with encouraging results. This paper reviews the achievements and current status of radionuclide remediation through biosorption which will provide insights into this research frontier. This paper reviews the achievements and the current status of radionuclide remediation through biosorption. To attract more usage of biosorption technology, some strategies have to be developed where further processing of biosorbent can be done to regenerate the biomass and then convert the recovered radionuclide into a usable form. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

Suganthi L.,Anna University | Samuel A.A.,Vellore Institute of Technology
Renewable and Sustainable Energy Reviews | Year: 2012

Energy is vital for sustainable development of any nation - be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management. © 2011 Elsevier Ltd. All rights reserved. Source

Das N.,Vellore Institute of Technology
Hydrometallurgy | Year: 2010

Recovery of precious metals like gold, silver, palladium platinum etc. is interesting due to its high market prices along with various industrial applications. Conventional technologies viz. ion exchange, chemical binding, surface precipitation etc. which been have been developed for the recovery of such metals are not economically attractive. Biosorption represents a biotechnological innovation as well as a cost effective excellent tool for recovery of precious metals from aqueous solutions. A variety of biomaterials are known to bind the precious metals including algae, fungi, bacteria actinomycetes, yeast etc. along with some biopolymers and biowaste materials.The metal binding mechanism , as well as the parameters influencing the uptake of precious metals and isotherm modeling are presented. This article provides an overview of past achievements and present scenario of biosorption studies carried out on the use of some promising biosorbents which could serve as an economical means for recovering precious metals. The present review also highlights the use of biosorbents in real situations and hopes to provide insights into this research frontier. © 2010 Elsevier B.V. All rights reserved. Source

Thangam A.,Vellore Institute of Technology
International Journal of Production Economics | Year: 2012

Many researchers have assumed that a retailer announces price discount, to motivate market sales, when he has competition in markets, unanticipated surplus in inventory, or change in the production run of a product. But, in real life situations, there are retailers who announce price discount offer under advance payment (AP) scheme prior to the selling period. Due to the advancement of internet and on-line money transactions, the AP scheme is common and useful to decrease the estimation error in demand and to increase the market sales. When the items are arrived to the inventory, the priority will be given to the customers who use AP scheme. This paper considers a supply chain where the supplier provides the retailer a full trade credit period for payments whereas the retailer offers the partial trade credit to his customers. I intend to develop an economic-order-quantity (EOQ)-based model with perishable items in order to investigate the retailers inventory system as a cost minimization problem under AP scheme and two-echelon trade credit option. Mathematical theorems are developed to determine optimal price discounting and lot-sizing policies and a lot of managerial phenomena are obtained through numerical examples. © 2012 Elsevier B.V. All rights reserved. Source

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