In this paper we propose a methodology based on a genetic algorithm (GA) to automate the design of combinational logic circuits in which we aim to minimize the total number of gates used. Our results are compared against those produced by human designers and by another GA-based approach. We also analyze the importance of using a non-binary representation in this problem despite the commonly acc...

Background: Autism Spectrum Disorder (ASD) occurs based on the continuous deficit in a person’s verbal skills, visual, auditory, touch, and social behavior. Over the last two decades, one of the most important approaches in studying brain functions in autistic persons is using functional Magnetic Resonance Imaging (fMRI). Objectives: It is common to use all brain regions in functional extracti...

a method based on the genetic algorithm (ga) was developed to study the phase behavior of multicomponent and multiphase systems. upon application of the ga to the thermodynamic models which are commonly used to study the vle, vlle and lle phase equilibria, the physically meaningful values for the binary interaction parameters (bip) of the models were obtained. using the method proposed in this ...

Neural network tree (NNTree) is a hybrid learning model. Currently We have proposed a simplified multiple objective optimization based genetic algorithm for evolving such kind of NNTrees and shown through experments that an NNTree can be interpreted easily if the number of inputs for each expert neural network (ENN) is limited. One problem remained is that for those problems the input features ...

Today due to increasing development and importance of petroleum activities andmarine transport as well as due to the mining of seabed, building activities such as construction of docks, platforms and structures as those in coastal areas and oceans has increased significantly. Concrete strength as one of the most important necessary parameters for designing, depends on many factors such as mixtu...

In this paper, a exible yet eecient algorithm for solving engineering design optimization problems is presented. The algorithm is developed based on both binary-coded and real-coded genetic algorithms (GAs). Since both GAs are used, the variables involving discrete, continuous, and zero-one variables are handled quite eeciently. The algorithm restricts its search only to the permissible values ...

This study is focused on the development of a systematic computational approach which implements Genetic Algorithm (GA) to find the optimal rigorous kinetic models.A general Kinetic model for hydrogenolysis of dibenzothiophene (DBT) based on Langmuir-Hinshelwood type has been obtained from open literature. This model consists of eight continuous parameters(e.g., Arrhenus  and Van't...

This paper studies a facility location model with fuzzy random parameters and its swarm intelligence approach. A Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRFLM) is built in which both the costs and demands are assumed to be fuzzy random variables, and the capacity of each facility is unfixed but a decision variable assuming continuous values. Under this setting, the V...