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The Ant System: Optimization by a colony of cooperating agents

by Marco Dorigo, Vittorio Maniezzo, Alberto Colorni - IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS-PART B , 1996
"... An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call Ant System. We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation ..."
Abstract - Cited by 1300 (46 self) - Add to MetaCart
An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call Ant System. We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed

Multi-Level Ant Colony Algorithm for Optimal Placement of Capacitors in Distribution Systems

by Rajeev Annaluru, Sanjoy Das, Ani Pahwa
"... Absfrocl-In this paper, an ant colony algorithm is proposed to determine the optimal locations and ratings of capacitors io B distribution network far reactive power compensation. The approach is multilevel. Two separate tables of pheromones PTO maintained by the algorithm. Ants generate solution st ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Absfrocl-In this paper, an ant colony algorithm is proposed to determine the optimal locations and ratings of capacitors io B distribution network far reactive power compensation. The approach is multilevel. Two separate tables of pheromones PTO maintained by the algorithm. Ants generate solution

The hyper-cube framework for ant colony optimization

by Christian Blum, Marco Dorigo , 2004
"... Ant colony optimization is a metaheuristic approach belonging to the class of model-based search algorithms. In this paper, we propose a new framework for implementing ant colony optimization algorithms called the hyper-cube framework for ant colony optimization. In contrast to the usual way of impl ..."
Abstract - Cited by 71 (22 self) - Add to MetaCart
Ant colony optimization is a metaheuristic approach belonging to the class of model-based search algorithms. In this paper, we propose a new framework for implementing ant colony optimization algorithms called the hyper-cube framework for ant colony optimization. In contrast to the usual way

Pheromone Evaluation in Ant Colony Optimization

by D. Merkle, M. Middendorf, H. Schmeck - Proceeding of the Third AsiaPaci c Conference on Simulated Evolution and Learning (SEAL2000 , 2000
"... In Ant Colony Optimization (ACO) artificial ants communicate by laying synthetic pheromone along the edges on their path through a decision graph. This attracts following ants so that they will likely search in the same region of the search space. The problem of how the pheromone information should ..."
Abstract - Cited by 3 (2 self) - Add to MetaCart
In Ant Colony Optimization (ACO) artificial ants communicate by laying synthetic pheromone along the edges on their path through a decision graph. This attracts following ants so that they will likely search in the same region of the search space. The problem of how the pheromone information should

MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows

by Luca Maria Gambardella, Éric Taillard, Giovanni Agazzi - New Ideas in Optimization , 1999
"... MACS-VRPTW, an Ant Colony Optimization based approach useful to solve vehicle routing problems with time windows is presented. MACS-VRPTW is organized with a hierarchy of artificial ant colonies designed to successively optimize a multiple objective function: the first colony minimizes the number of ..."
Abstract - Cited by 162 (6 self) - Add to MetaCart
MACS-VRPTW, an Ant Colony Optimization based approach useful to solve vehicle routing problems with time windows is presented. MACS-VRPTW is organized with a hierarchy of artificial ant colonies designed to successively optimize a multiple objective function: the first colony minimizes the number

Ant Colony Optimization for Resource-Constrained Project Scheduling

by Daniel Merkle, Martin Middendorf, Hartmut Schmeck - IEEE Transactions on Evolutionary Computation , 2000
"... An ant colony optimization approach (ACO) for the resource-constrained project scheduling problem (RCPSP) is presented. Combinations of two pheromone evaluation methods are used by the ants to find new solutions. We tested our ACO algorithm on a set of large benchmark problems from the PSPLIB. Compa ..."
Abstract - Cited by 100 (9 self) - Add to MetaCart
An ant colony optimization approach (ACO) for the resource-constrained project scheduling problem (RCPSP) is presented. Combinations of two pheromone evaluation methods are used by the ants to find new solutions. We tested our ACO algorithm on a set of large benchmark problems from the PSPLIB

Parallelization Strategies for Ant Colony Optimization

by Thomas Stützle - Proceedings of PPSN-V, Fifth International Conference on Parallel Problem Solving from Nature , 1998
"... . Ant Colony Optimization (ACO) is a new population oriented search metaphor that has been successfully applied to NP-hard combinatorial optimization problems. In this paper we discuss parallelization strategies for Ant Colony Optimization algorithms. We empirically test the most simple strategy, th ..."
Abstract - Cited by 40 (6 self) - Add to MetaCart
. Ant Colony Optimization (ACO) is a new population oriented search metaphor that has been successfully applied to NP-hard combinatorial optimization problems. In this paper we discuss parallelization strategies for Ant Colony Optimization algorithms. We empirically test the most simple strategy

An Ant Colony Optimization Based Approach for Feature Selection

by Ahmed Ai-Ani
"... Abstract This paper presents a new feature subset selection algorithm based on the Ant Colony Optimization (ACO). ACO is a metaheuristic inspired by the behaviour of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by utilizing distributed computing, ..."
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Abstract This paper presents a new feature subset selection algorithm based on the Ant Colony Optimization (ACO). ACO is a metaheuristic inspired by the behaviour of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by utilizing distributed computing

A concise overview of applications of ant colony optimization

by Thomas Stützle , Manuel López-Ibáñez , Marco Dorigo - In Encyclopedia of Operations Research and Management Science , 2011
"... Ant Colony Optimization (ACO) Despite being one of the youngest metaheuristics, the number of applications of ACO algorithms is very large. In principle, ACO can be applied to any combinatorial optimization problem for which some iterative solution construction mechanism can be conceived. Most app ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
) is the capacitated minimum spanning tree problem (CMST), which has been effectively tackled by a hybrid ACO algorithm [44] based on a previous ACO algorithm for the CVRP Finally, a class of problems for which ACO has recently shown competitive results is that of multi-level lot-sizing with Assignment and layout

A hybrid ant colony optimization algorithm . . .

by Gajanan Aochar, Roshni Ade , 2015
"... Ant colony optimisation (ACO) could be a comparatively new random heuristic approach for determination optimisation issues. Furthermore, This paper extend these implementations with two local search methods and we compare two heuristics that guide the HACO algorithms. However, relatively few results ..."
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Ant colony optimisation (ACO) could be a comparatively new random heuristic approach for determination optimisation issues. Furthermore, This paper extend these implementations with two local search methods and we compare two heuristics that guide the HACO algorithms. However, relatively few
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