Most real world engineering design problems, such as cross-country water mains, include combinations of continuous, discrete, and binary value decision variables. Very often, the binary decision variables associate with the presence and/or absence of some nominated alternatives or project’s components. This study extends an existing continuous Ant Colony Optimization (ACO) algorithm to simultan...

With the advancement of Computer Networks and increase in size of databases, the decentralization of databases has led to the development of Distributed Database over multiple machines where distribution of the database is Transparent to the users. The query optimization problem in large-scale distributed databases is NP-hard in nature and difficult to solve. Research is being carried out to fi...

A hybrid population based Ant Colony Optimization (ACO) algorithm PFold-P-ACO for protein folding in the HP model is proposed in this paper. This is the first population based ACO algorithm in the bioinformatics. It is shown experimentally that the algorithms achieves on nearly all test sequences at least comparable results to other state of the art algorithms. Compared to the state of the art ...

Although an ant is a simple creature, collectively a colony of ants performs useful tasks such as finding the shortest path to a food source and sharing this information with other ants by depositing pheromone. In the field of ant colony optimization (ACO), models of collective intelligence of ants are transformed into useful optimization techniques that find applications in computer networking...

In this paper we try to introduce the Ant Colony Optimization (ACO) and its application in Economic Dispatch ED). In the step one we present theory and performance of ant colony and its history and its application in various applications and how work the ant colony algorithm. In step two we present ant colony optimization include Basic Concept, Ant Searching Behavior, Path Retracing and Pheromo...

This paper presents an improved clustering algorithm with Ant Colony optimization (ACO) based on dynamical pheromones. Pheromone is an important factor for the performance of ACO algorithms. Two strategies based on adaptive pheromones which improved performance are introduced in this paper. One is to adjust the rate of pheromone evaporation dynamically, named as  , and the other is to adjust t...

Ant Colony Optimization (ACO) is a promising new approach to combinatorial optimization. Here ACO is applied to the traveling salesman problem (TSP). Using a genetic algorithm (GA) to nd the best set of parameters, we demonstrate the good performance of ACO in nding good solutions

Software testing is very important for ensuring software quality in organizations. In fact, the quality of test suite plays an important role for the success of software testing .Ant colony optimization (ACO) which is a part of Swarm Intelligence is used to settle optimization problem. This paper attempts to provide ideas of Test Case Selection and Prioritization which Ant Colony Optimization w...

Ant colony optimization is an ant algorithm framework that took inspiration from foraging behavior of ant colonies. Indeed, ACO algorithms use a chemical communication, represented by pheromone trails, to build good solutions. However, ants involve different communication channels to interact. Thus, this paper introduces the acoustic communication between ants while they are foraging. This proc...