Ant colony

Ants are one of the most amazing groups of insects in the animal kingdom. This is because they are social insects. Ants form organized and structured colonies or nests consisting of millions of individuals. Colonies of ant species will work together and form super-colonies, covering a very large area of land. Their colonies are described as super organisms as they appear to work and survive as a single entity. Ants have captured almost every area on Earth. They make up to 15% of the total

Abstract Ant colony optimization is a technique for solving problem which are hard in nature. These kinds of problems need only the optimal solution. ACO provide a solution based on the behaviour of ants searching for food. This paper list out various techniques used to solve such problems and their advantages, disadvantages. Through this review we identify some suggestion for solving NP hard problem. Keywords :Ant colony optimization, NP hard, stigmergy, Pheromone, optimal , heuristics 1. Introduction

In the proposed approach particle swarm optimization along with ant colony optimization is used for setting of control variables for optimal power flow problem. The proposed approach is tested and examined in standard IEEE 30 bus test system. The various objective functions involved are fuel cost minimization, voltage profile improvement and transmission loss reduction. This proposed approach overcomes the disadvantages of ant colony optimization such as premature convergence and stagnating output

In this paper we will find solution using ant colony optimization. This process is based on probability technique to find results of computational problem. It is a set of software agents called artificial ants to find solution to a given problem. When ACO is applied then problem is changed into the problem of finding the best way on the weighted graph. The artificial ants will increasingly build the solution path via traversing through the whole graph. The solution is biased by the pheromone model

1.6 Ant Colony Optimization: 1.6.1 Introduction The conception of massive Gordian behavior emerging from the behavior of many relatively simple units, and the dealings with them, is fundamental to the field of Artificial Intelligence. The growing understanding of such systems offers the prospect of creating artificial systems which are controlled by such significant shared behavior; in particular, we believe that the sweating of this concept might lead to entirely new channels for the pilotage

GAVNS: Guided Ant Colony Optimization based Variable Neighborhood Search for Optimistic Load Balancing in Grid Computing Gurveer Kaur Brar1, Amit Chhabra2 1 Guru Nanak Dev University, Amritsar Punjab, India gurveer.dhillon43@gmail.com, amit.cse@gndu.ac.in Abstract Grid Computing resolves high performance computing and throughput issues through sharing of resources. These resources are heterogeneous in nature and geographically distributed to develop large scale applications. Scheduling

3.3 Scheduling in Ant Colony CPU scheduling is the basis of multiprogrammed operating systems. By switching the CPU among processes, the operating system can make the computer more productive. In a single-processor system, only one process can run at a time; any others must wait until the CPU is free and can be rescheduled. The objective of multiprogramming is to have some process running at all times, to maximize CPU utilization. The idea is relatively simple. A process is executed until it must

“an ant on a tablecloth…” Then the ant bumps into a day drowsy moth that is much larger than him. The ant seems a tad bit jealous that the moth lacks the amount of responsibility that ants are burdened with. The ant thinks that if the moth were one of his own race he’d chastise him and send him back to work. He describes how

issues like death. The poem begins with a description of a scene familiar to many, "an ant on a tablecloth…" Then the ant bumps into a day drowsy moth that is much larger than him. The ant seems a tad bit jealous that the moth lacks the amount of responsibility that ants are burdened with. The ant thinks that if the moth were one of his own race he'd chastise him and send him back to work. He describes how the ant society is much more sophisticated and

Harvester ants, who after 5 years reach it’s breakpoint, and continues on rather efficiently because of it’s limits. Once those five years pass the ant colony is limited to 10,000 ants, with the Queen reproducing specifically just to replace the worker ants that die off after a year. Just like neurons, all of the ants in a specific colony strive for one goal. That’s what makes the brain, and ant colonies so intelligent. Each neuron only has one task, but through a vast network of neurons and ants, bigger