Future Generation Computer Systems
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Ant Colony Optimization
A study of drift analysis for estimating computation time of evolutionary algorithms
Natural Computing: an international journal
On the Choice of the Offspring Population Size in Evolutionary Algorithms
Evolutionary Computation
A rigorous analysis of the compact genetic algorithm for linear functions
Natural Computing: an international journal
On the runtime analysis of the 1-ANT ACO algorithm
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Information Processing Letters
Theoretical analysis of fitness-proportional selection: landscapes and efficiency
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Runtime analysis of an ant colony optimization algorithm for TSP instances
IEEE Transactions on Evolutionary Computation
Runtime analysis of a binary particle swarm optimizer
Theoretical Computer Science
Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation
Algorithmica - Special Issue: Theory of Evolutionary Computation
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
Running time analysis of Ant Colony Optimization for shortest path problems
Journal of Discrete Algorithms
On the analysis of the simple genetic algorithm
Proceedings of the 14th annual conference on Genetic and evolutionary computation
The choice of the offspring population size in the (1,λ) EA
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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
Runtime analysis of ant colony optimization on dynamic shortest path problems
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Ant colony optimization (ACO) has found many applications in different problem domains. We carry out a first rigorous runtime analysis of ACO with iteration-best update, where the best solution in the each iteration is reinforced. This is similar to comma selection in evolutionary algorithms. We compare ACO to evolutionary algorithms for which it is well known that an offspring size of Ω(log n), n the problem dimension, is necessary to optimize even simple functions like ONEMAX. In sharp contrast, ACO is efficient on ONEMAX even for the smallest possible number of two ants. Remarkably, this only holds if the pheromone evaporation rate is small enough; the collective memory of many ants stored in the pheromones makes up for the small number of ants. We further prove an exponential lower bound for ACO with iteration-best update that depends on a trade-off between the number of ants and the evaporation rate.