This paper presents an ant colony optimization methodology for optimally clustering N objects into K clusters. The algorithm employs distributed agents which. AbstractAnt-based clustering is a biologically inspired data. Multi-ant colonies approach for clustering data that consists of some parallel.based on ant colony to solve the unsupervised clustering. Index TermsAnt colony optimization, Clu...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

This paper presents a robust hybrid improved dolphin echolocation and ant colony optimization algorithm (IDEACO) for optimization of truss structures with discrete sizing variables. The dolphin echolocation (DE) is inspired by the navigation and hunting behavior of dolphins. An improved version of dolphin echolocation (IDE), as the main engine, is proposed and uses the positive attributes of an...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...

This paper describes GRAF-ANT (Graphical Framework for Ant Colony Optimization), an objectoriented C# framework for developing ant colony systems that we have developed. While developing this framework, abstractions that are necessary for ant colony optimization algorithms were analyzed, as well as the features that their implementing classes should have. During creation of these classes, sever...

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...

Recent days, research in wireless network becomes major area for the past few decades. In wireless routing many routing methods such as table driven, source driven; many characteristics such as reactive routing, proactive routing; many routing algorithms such as dijikstra’s shortest path, distributed bell-man ford algorithm are proposed in the literature. For effective wireless routing, the rec...

An algorithm for edge detection with low contrast image using improved ant colony optimization is proposed in this paper. In edge detection, some parts of the edge are disappeared or disconnected because of low contrast in their intensities. This paper concentrates to this low-contrast problem. To detect these pixels, the direction tendency of edge lines is computed and ant colony optimization ...

abstract: in this paper, optimization of boeing 747 wing has been accomplished for cruise condition (mach number=0.85, flight altitude=35000 ft), where an optimal wing shape is proposed. objective functions are minimization of wing weight and drag force that as well as confining design parameters, two functional constrains are applied. the first functional constrain is fuel tank volume in the a...