In this paper multiobjective optimization problem simultaneously optimized using hybrid PS-ACO algorithm has been attempted. The methodology used in this paper is based upon the information sharing and movement of swarms or particles in a search space, and further applying ACO on the result obtained by the PSO. Multiobjective optimization problems are present at physical design level at partiti...

The apical hook of dark-grown dicotyledonous seedlings is a protective structure resulting from an inhibition of cell elongation on the inner portion of the hook. This differential growth response is mediated by ethylene. Expression of the gene encoding 1-aminocyclopropane-1-carboxylate oxidase (ACO), the terminal enzyme in ethylene biosynthesis, is induced by ethylene via a positive feedback l...

Abstract Differential evolution algorithm (DE) is a well-known population-based method for solving continuous optimization problems. It has simple structure and easy to adapt wide range of applications. However, with suitable population sizes, its performance depends on the two main control parameters: scaling factor ( F ) crossover rate CR ). The classical DE can achieve high by time-consuming...

optimization of reservoir parameters is an important issue in petroleum exploration and production. the ant colony optimization(aco) is a recent approach to solve discrete and continuous optimization problems. in this paper, the ant colony optimization is usedas an intelligent tool to estimate reservoir rock properties. the methodology is illustrated by using a case study on shear wave velocity...

A two-stage optimization method is presented by employing the evolutionary structural optimization (ESO) and ant colony optimization (ACO), which is called ESO-ACO method. To implement ESO-ACO, size optimization is performed using ESO, first. Then, the outcomes of ESO are employed to enhance ACO. In optimization process, the weight of double layer grid is minimized under various constraints whi...

This paper presents improved Ant Colony Optimization (ACO) algorithms for data mining. The goal of the algorithms is to extract classification rules from data. The traditional Ant Colony Optimization algorithm is enhanced with genetic operators to develop improved ACO algorithms. The genetic operators like crossover, mutation are used to develop Ant Colony Optimization with Crossover (ACOC), AC...

We examine the power spectrum of clusters in the Press-Schechter (PS) theory and in N-body simulations to see how the power spectrum of clusters is related to the power spectrum of matter density fluctuations in the Universe. An analytic model for the power spectrum of clusters for their given number density is presented, both for real space and redshift space. We test this model against result...

Isolation of a recessive aco (androcarpel organ) mutation in opium poppy Papaver somniferum, is described. The aco (aco aco) mutant plants form androcarpels in place of inner whorl stamens in their flowers. The abnormal flowers are self-fertile, as stamens in the outer whorl are normal. In aco mutant the calyx, corolla and syncarpous gynoecium are formed like in the wild type ACO plants. The an...

In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ant are introduced into the ACO. The modifi...