Ant Colony Optimization (ACO) algorithm has evolved as the most popular way to attack the combinatorial problems. The ACO algorithm employs multi agents called ants that are capable of finding optimal solution for a given problem instances. These ants at each step of the computation make probabilistic choices to include good solution component in partially 1 / 4

This paper studies the one-operator m-machine flow shop scheduling problem with the objective of minimizing the total completion time. In this problem, the processing of jobs and setup of machines require the continuous presence of a single operator. We compare three different mathematical formulations and propose an ant colony optimization based metaheuristic to solve this flow shop scheduling...

Ant Colony Optimization (ACO) algorithm has evolved as the most popular way to attack the combinatorial problems. The ACO algorithm employs multi agents called ants that are capable of finding optimal solution for a given problem instances. These ants at each step of the computation make probabilistic choices to include good solution component in partially 1 / 4

A multi-type ant colony optimization (MACO) method for optimal land use allocation in large areas Xiaoping Liu a , Xia Li a , Xun Shi b , Kangning Huang a & Yilun Liu a a School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, 510275, Guangdong, PR China b Department of Geography, Dartmouth College, Hanover, NH, 0375...

This paper presents an ant colony optimization metaheuristic for the solution of an industrial scheduling problem in an aluminum casting center. We present an efficient representation of a continuous horizontal casting process which takes account of a number of objectives that are important to the scheduler. We have incorporated the methods proposed in software that has been implemented in the ...

through a collection of cooperative agents called ants, the near optimal solution to the multi-reservoir operation problem may be effectively achieved employing ant colony optimization algorithms (acoas). the problem is approached by considering a finite operating horizon, classifying the possible releases from the reservoir(s) into pre-determined intervals, and projecting the problem on a grap...

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...

-The ant colony optimization takes insipiration from the foraging behavior of some ant species.These ants deposits pheromone on the ground in order to make some suitable path that should be followed by other members of the colony.The goal of this paper is to introduce ant colony optimization and to survey its most notable applications.In this paper we focus on some research efforts directed at ...

Ant colony optimization is a metaheuristic approach belonging to the model based search algorithm. It is a paradigm for designing metaheuristic algorithm for combinatorial problem. In this paper we discuss the Ant colony system. Ant colony system is one of the best algorithm of ant colony optimization. First we discuss the optimization,and one of the optimization problem is combinatiorial probl...