Narula Institute of Technology

About: Narula Institute of Technology is a based out in . It is known for research contribution in the topics: Quantum dot cellular automaton & Cognitive radio. The organization has 288 authors who have published 490 publications receiving 2258 citations. The organization is also known as: NiT.

A genetic algorithm based stochastic simulation approach to chance constrained interval valued multiobjective decision making problems

Abstract: This article presents how the stochastic simulation through genetic algorithm (GA) can be used to modeling and solving chance constrained interval valued multiobjective decision making (MODM) problems. In the proposed method, a stochastic simulation approach to the chance constraints is employed for interval valued goal representation of the objectives as well as decision identification through the use of an GA method in an inexact decision making context. In the executable goal programming (GP) model of the problem, both the aspects of the GP, minsum GP and minmax GP [1], are addressed within goal achievement function for minimizing possible regrets associated with the deviational variables of the defined goals for goal achievement within the target intervals specified in the decision making environment. A numerical example is solved and a comparison is made with the conventional GP approach.

Bio-inspired computational technique to multiobjective optimal planning of electric power generation and dispatch

Abstract: In this paper, a Genetic Algorithm (GA) based fuzzy goal programming (FGP) technique to multiobjective optimal planning of electric power generation and dispatch problem in power system operation and planning phases is presented. In the proposed approach, fuel cost, environmental emission and voltage deviation objectives of optimal power flow calculation are fuzzily described. In the solution process, the GA method is used in an iterative manner for satisficing the goal levels on the basis of needs and desires of the power system operation and planning perspective. In the GA based solution search process, the conventional Roulette wheel selection scheme, single-point crossover and bit-by-bit mutation are taken into consideration to reach a satisfactory decision. The developed method has been tested on IEEE 6-generator 30-bus System.

The simulation and analysis of modified LEACH protocol for wireless sensor networks using TOSSIM

Abstract: The most important routing protocol LEACH of wireless sensor networks (WSNs) has been incorporated by W. Heinzelman. LEACH uses the concept of dynamic clustering when sensor nodes are deploying randomly. Therefore the number of cluster impact on the network. This paper describes the network quality that depends on the optimum selection of number of clusterhead in Modified LEACH protocol using new simulator TOSSIM. hi this paper we discussed and explain the comparison of data packet broadcasting, energy consumption and dead node of LEACH and Modified LEACH respectively. Simulation result shows Modified LEACH performs better than LEACH for extending overall network performances.

A genetic algorithm based fuzzy goal programming solution approach to chance constrained bilevel programming problems

Abstract: In this article, a genetic algorithm (GA) based fuzzy goal programming (FGP) procedure for solving bilevel programming problems (BLPPs) having the chance constraints in large hierarchical decision problems is presented.