A case-based reasoning (CBR) knowledge base has been incorporated into a Micro-Electro-Mechanical Systems (MEMS) design tool that uses a multi-objective genetic algorithm (MOGA) to synthesize and optimize conceptual designs. CBR utilizes previously successful MEMS designs and sub-assemblies as building blocks stored in an indexed case library, which serves as the knowledge base for the synthesi...

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...

7253 | P a g e C o u n c i l f o r I n n o v a t i v e R e s e a r c h A u g u s t , 2 0 1 6 w w w . c i r w o r l d . c o m POWER EFFICIENT TASK SCHEDULING MECHANISM IN CLOUD ENVIRONMENT: A REVIEW Abhilasha , Dr. Anupama Gupta (2) (1) Research Scholar, Department of Computer Engineering, LLRIET, Moga. [email protected] (2) H.O.D, Department of Computer Science & Engineering, LLRIET, Mog...

Obtaining the fullest possible representation of solutions to a multi-objective optimization problem has been a major concern in MultiObjective Genetic Algorithms (MOGAs). This is because a MOGA, due to its nature, usually produces several clusters of solutions that does not cover the whole range of Pareto frontier. This poster paper indroduces an overview of a new approach, one that aims at ob...

In this work we consider the design of neural network and Takagi Sugeno fuzzy logic controller, TSFLC, with Multi-Obejctive Genetic Algorithm, MOGA. For the neural network, the MOGA has to minimize three objectives, the cumulated error, the number of neurons in the hidden layer and the number and type of inputs to the network. In the case of the TS FLC, the objectives are the cumulated error an...

Multi-Objective Genetic Algorithm (MOGA) is a new approach for association rule mining in the market-basket type databases. Finding the frequent itemsets is the most resource-consuming phase in association rule mining, and always does some extra comparisons against the whole database. This paper proposes a new algorithm, Cluster-Based MultiObjective Genetic Algorithm (CBMOGA) which optimizes th...

The Multi Objective Genetic Algorithms (MOGAs) are one of the most widely used techniques that have the capability to find the solution to the problem having multiple conflicting objectives like Intrusion Detection. It is a population based technique capable of producing a set of non-inferior solutions that exhibit the classification trade-offs for the user. This capability of MOGA can be explo...

Two techniques are combined during the design of an optimal controller: Linear Matrix Inequalities (LMIs) and Multi-objective Genetic Algorithms (MOGAs). In this paper the LMI optimization technique is used to obtain a single controller while MOGA is used to convert the controller design into a multi-objective optimization procedure. The combination of these techniques is proposed in this docum...

This paper presents a novel method to solve non-linear time-cost tradeoff (TCT) problem of real world engineering projects. Multiobjective genetic algorithm (MOGA) is employed to search for optimal TCT profile. Applicability of ANN based model for rapid estimation of time-cost relationship by invoking its function approximation capability is investigated. ANN models are then integrated with MOG...

Multi-objective optimization (MO) has been an active area of research in the last two decades. In multi-objective genetic algorithm (MOGA), the quality of newly generated offspring of the population will directly affect the performance of finding the Pareto optimum. In this paper, an improved MOGA, named SMGA, is proposed for solving multi-objective optimization problems. To increase efficiency...