Multi-population GAs are found to be more efficient than Standard Genetic Algorithm (SGA) in terms of convergence as well as reliability of results. Nomadic Genetic Algorithm (NGA) is a kind of multi-population GA wherein individuals keep migrating from one subpopulation to another based on their fitness. It has been proved to be very effective in improving the performance of single population ...

This paper considers the problem of minimizing the response time for a given database workload by a proper choice of indexes. This problem is NP-hard and known in the literature as the Index Selection Problem (ISP). We propose a genetic algorithm (GA) for solving the ISP. Computational results of the GA on standard ISP instances are compared to branchand-cut method and its initialisation heuris...

Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, w...

Let G = (V,E), V {1,2,...,n}, be a simple connected graph of order n, size m with vertex degree sequence d1 ? d2 ... dn > 0, di d(vi). The geometric-arithmetic topological index is defined as GA(G) i~j 2? didj/di+dj, whereas the coindex GA?(G) i~/j 2 didj/di+dj . New lower bounds for and in terms some parameters other invariants are obtained.

This paper proposes optimal task decomposition agents (OTDAS) of the multiagent power plant control system. The goal, decision-making and operation of the OTDAS are introduced. The OTDAS optimally decompose the task of power plant control system through an optimization agent and a decomposition agent. The optimization agent makes decision using Genetic Algorithm (GA). The results of the OTDAS s...

In investment market, investors often pay attention to investment portfolio selection and asset allocation under market risk. Thus, this study presents a two-stage method of investment portfolio based on soft computing techniques. The first stage uses data envelopment analysis to select most profitable funds, while hybrid of genetic algorithm (GA) and particle swarm optimization (PSO)is propose...

Traditionally, scheduling and process planning are considered as two different functions in a manufacturing environment. In this paper we consider the simultaneous selection of best process plan and scheduling of jobs in a job shop environment. We propose a spreadsheet based genetic algorithm (GA) to solve this class of problem. The shop model is built in Microsoft Excel spreadsheet to find the...

In this work, quantitative structure-retention relationship (QSRR) approaches were applied for modeling and prediction of the retention index of 282 amino acids (AAs) and carboxylic acids (CAs). Descriptors that were used to encode structural features of molecules in a data set were calculated by using the Dragon software. The genetic algorithm (GA) and stepwise multiple linear regression (MLR)...