Runtime analysis of a binary particle swarm optimizer
Theoretical Computer Science
Ant Colony Optimization and the minimum spanning tree problem
Theoretical Computer Science
A few ants are enough: ACO with iteration-best update
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Ant colony optimization and the minimum cut problem
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Ant colony optimization for stochastic shortest path problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Theoretical properties of two ACO approaches for the traveling salesman problem
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Runtime analysis of the 1-ANT ant colony optimizer
Theoretical Computer Science
Using markov-chain mixing time estimates for the analysis of ant colony optimization
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Simple max-min ant systems and the optimization of linear pseudo-boolean functions
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Two-stage updating pheromone for invariant ant colony optimization algorithm
Expert Systems with Applications: An International Journal
Running time analysis of Ant Colony Optimization for shortest path problems
Journal of Discrete Algorithms
Analysis of an iterated local search algorithm for vertex cover in sparse random graphs
Theoretical Computer Science
The use of tail inequalities on the probable computational time of randomized search heuristics
Theoretical Computer Science
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Energy efficient ant colony algorithms for data aggregation in wireless sensor networks
Journal of Computer and System Sciences
ACO beats EA on a dynamic pseudo-boolean function
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Black-box complexities of combinatorial problems
Theoretical Computer Science
EA'11 Proceedings of the 10th international conference on Artificial Evolution
Annals of Mathematics and Artificial Intelligence
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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.