Results 1 - 10 of 110

AntNet: A Mobile Agents Approach to Adaptive Routing

by Gianni Di Caro, Marco Dorigo , 1997
"... This paper introduces AntNet, a new routing algorithm for communications networks. AntNet is an adaptive, distributed, mobile-agents-based algorithm whichwas inspired by recentwork on the ant colony metaphor. We apply AntNet to a datagram network and compare it with both static and adaptive state-of ..."
Abstract - Cited by 135 (6 self) - Add to MetaCart
This paper introduces AntNet, a new routing algorithm for communications networks. AntNet is an adaptive, distributed, mobile-agents-based algorithm whichwas inspired by recentwork on the ant colony metaphor. We apply AntNet to a datagram network and compare it with both static and adaptive state-of-the-art routing algorithms. We ran experiments for various paradigmatic temporal and spatial traffic distributions. AntNet showed both very good performance and robustness under all the experimental conditions with respect to its competitors.

Model-based search for combinatorial optimization

by Mark Zlochin, Marco Dorigo , 2001
"... Abstract In this paper we introduce model-based search as a unifying framework accommodating some recently proposed heuristics for combinatorial optimization such as ant colony optimization, stochastic gradient ascent, cross-entropy and estimation of distribution methods. We discuss similarities as ..."
Abstract - Cited by 64 (12 self) - Add to MetaCart
Abstract In this paper we introduce model-based search as a unifying framework accommodating some recently proposed heuristics for combinatorial optimization such as ant colony optimization, stochastic gradient ascent, cross-entropy and estimation of distribution methods. We discuss similarities as well as distinctive features of each method, propose some extensions and present a comparative experimental study of these algorithms. 1
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An Ant Colony System Hybridized With A New Local Search For The Sequential Ordering Problem

by Luca Maria Gambardella, Marco Dorigo , 2000
"... We present a new local optimizer called SOP-3-exchange for the sequential ordering problem that extends a local search for the traveling salesman problem to handle multiple constraints directly without increasing computational complexity. An algorithm that combines the SOP-3-exchange with an Ant Col ..."
Abstract - Cited by 62 (14 self) - Add to MetaCart
We present a new local optimizer called SOP-3-exchange for the sequential ordering problem that extends a local search for the traveling salesman problem to handle multiple constraints directly without increasing computational complexity. An algorithm that combines the SOP-3-exchange with an Ant Colony Optimization algorithm is described and we present experimental evidence that the resulting algorithm is more effective than existing methods for the problem. The best-known results for many of a standard test set of 22 problems are improved using the SOP-3-exchange with our Ant Colony Optimization algorithm or in combination with the MPO/AI algorithm (Chen and Smith 1996).

Ant Colonies for the QAP

by L.M. Gambardella, D. Taillard, M. Dorigo , 1998
"... This paper presents HAS-QAP, a hybrid ant colony system coupled with a local search, applied to the ..."
Abstract - Cited by 61 (7 self) - Add to MetaCart
This paper presents HAS-QAP, a hybrid ant colony system coupled with a local search, applied to the

HAS-SOP: Hybrid Ant System For The Sequential Ordering Problem

by Luca Maria Gambardella, Marco Dorigo , 1997
"... We present HAS-SOP, a new approach to solving sequential ordering problems. HAS-SOP combines the ant colony algorithm, a population-based metaheuristic, with a new local optimizer, an extension of a TSP heuristic which directly handles multiple constraints without increasing computational complexity ..."
Abstract - Cited by 51 (7 self) - Add to MetaCart
We present HAS-SOP, a new approach to solving sequential ordering problems. HAS-SOP combines the ant colony algorithm, a population-based metaheuristic, with a new local optimizer, an extension of a TSP heuristic which directly handles multiple constraints without increasing computational complexity. We compare different implementations of HASSOP and present a new data structure that improves system performance. Experimental results on a set of twenty-three test problems taken from the TSPLIB show that HAS-SOP outperforms existing methods both in terms of solution quality and computation time. Moreover, HAS-SOP improves most of the best known results for the considered problems.

Mobile agents for adaptive routing

by Gianni Di Caro, Marco Dorigo - In H. El-Rewini (Ed.), Proceedings of the 31st International Conference on System Sciences (HICSS-31 , 1998
"... This paper introduces AntNet, a new routing algorithm for telecommunication networks. AntNet is an adaptive, distributed, mobile-agents-based algorithm which was inspired byrecent work on the ant colony metaphor. We apply AntNet in a datagram network and compare it with both static and adaptive stat ..."
Abstract - Cited by 51 (5 self) - Add to MetaCart
This paper introduces AntNet, a new routing algorithm for telecommunication networks. AntNet is an adaptive, distributed, mobile-agents-based algorithm which was inspired byrecent work on the ant colony metaphor. We apply AntNet in a datagram network and compare it with both static and adaptive state-ofthe-art routing algorithms. We ran experiments for various paradigmatic temporal and spatial tra c distributions. AntNet showed both very good performances and robustness under all the experimental conditions with respect to its competitors. 1
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Runtime Analysis of a Simple Ant Colony Optimization Algorithm

by Frank Neumann, Carsten Witt - ELECTRONIC COLLOQUIUM ON COMPUTATIONAL COMPLEXITY, REPORT NO. 84 (2006) , 2006
"... Ant Colony Optimization (ACO) has become quite popular in recent years. In contrast to many successful applications, the theoretical foundation of this randomized search heuristic is rather weak. Building up such a theory is demanded to understand how these heuristics work as well as to come up with ..."
Abstract - Cited by 49 (13 self) - Add to MetaCart
Ant Colony Optimization (ACO) has become quite popular in recent years. In contrast to many successful applications, the theoretical foundation of this randomized search heuristic is rather weak. Building up such a theory is demanded to understand how these heuristics work as well as to come up with better algorithms for certain problems. Up to now, only convergence results have been achieved showing that optimal solutions can be obtained in finite time. We present the first runtime analysis of an ACO algorithm, which transfers many rigorous results with respect to the runtime of a simple evolutionary algorithm to our algorithm. Moreover, we examine the choice of the evaporation factor, a crucial parameter in ACO algorithms, in detail. By deriving new lower bounds on the tails of sums of independent Poisson trials, we determine the effect of the evaporation factor almost completely and prove a phase transition from exponential to polynomial runtime.

Towards Multi-Swarm Problem Solving in Networks

by Tony White , Bernard Pagurek - IN PROCEEDINGS OF THIRD INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS (ICMAS'98 , 1998
"... This paper describes how multiple interacting swarms of adaptive mobile agents can be used to solve problems in networks. The paper introduces a new architectural description for an agent that is chemically inspired and proposes chemical interaction as the principal mechanism for inter-swarm communi ..."
Abstract - Cited by 44 (4 self) - Add to MetaCart
This paper describes how multiple interacting swarms of adaptive mobile agents can be used to solve problems in networks. The paper introduces a new architectural description for an agent that is chemically inspired and proposes chemical interaction as the principal mechanism for inter-swarm communication. Agents within a given swarm have behavior that is inspired by the foraging activities of ants, with each agent capable of simple actions and knowledge of a global goal is not assumed. The creation of chemical trails is proposed as the primary mechanism used in distributed problem solving arising from self-organization of swarms of agents. The paper proposes that swarm chemistries can be engineered in order to apply the principal ideas of the Subsumption Architecture in the domain of mobile agents. The paper presents applications of the new architecture in the domain of communications networks and describes the essential elements of a mobile agent framework that is being considered fo...

The state problem for evolutionary testing

by Phil Mcminn, Mike Holcombe - Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’03 , 2003
"... Abstract. This paper shows how the presence of states in test objects can hinder or render impossible the search for test data using evolutionary testing. Additional guidance is required to find sequences of inputs that put the test object into some necessary state for certain test goals to become f ..."
Abstract - Cited by 43 (2 self) - Add to MetaCart
Abstract. This paper shows how the presence of states in test objects can hinder or render impossible the search for test data using evolutionary testing. Additional guidance is required to find sequences of inputs that put the test object into some necessary state for certain test goals to become feasible. It is shown that data dependency analysis can be used to identify program statements responsible for state transitions, and then argued that an additional search is needed to find required transition sequences. In order to be able to deal with complex examples, the use of ant colony optimization is proposed. The results of a simple initial experiment are reported. 1
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A graph-based Ant System and its convergence

by Walter J. Gutjahr - Future Generation Computing Systems , 2000
"... Abstract: A general framework for solving combinatorial optimization problems heuristically by the Ant System approach is developed. The framework is based on the concept of a construction graph, a graph assigned to an instance of the optimization problem under consideration, encoding feasible solut ..."
Abstract - Cited by 35 (1 self) - Add to MetaCart
Abstract: A general framework for solving combinatorial optimization problems heuristically by the Ant System approach is developed. The framework is based on the concept of a construction graph, a graph assigned to an instance of the optimization problem under consideration, encoding feasible solutions by walks. It is shown that under certain conditions, the solutions generated in each iteration of this Graph–based Ant System converge with a probability that can be made arbitrarily close to one to the optimal solution of the given problem instance.
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