Randomized algorithms
Future Generation Computer Systems
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Modeling the dynamics of ant colony optimization
Evolutionary Computation
Evolutionary Algorithms and the Maximum Matching Problem
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Ant Colony Optimization
A GENERALIZED CONVERGENCE RESULT FOR THE GRAPH-BASED ANT SYSTEM METAHEURISTIC
Probability in the Engineering and Informational Sciences
Crossover is provably essential for the Ising model on trees
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
On the Choice of the Offspring Population Size in Evolutionary Algorithms
Evolutionary Computation
Ant colony optimization theory: a survey
Theoretical Computer Science
Randomized local search, evolutionary algorithms, and the minimum spanning tree problem
Theoretical Computer Science
On the runtime analysis of the 1-ANT ACO algorithm
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Information Processing Letters
Speeding up evolutionary algorithms through asymmetric mutation operators
Evolutionary Computation
First steps to the runtime complexity analysis of ant colony optimization
Computers and Operations Research
How Single Ant ACO Systems Optimize Pseudo-Boolean Functions
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Ant Colony Optimization and the minimum spanning tree problem
Theoretical Computer Science
Theoretical properties of two ACO approaches for the traveling salesman problem
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Worst-case and average-case approximations by simple randomized search heuristics
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
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
Fixed budget computations: a different perspective on run time analysis
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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The runtime analysis of randomized search heuristics is a growing field where, in the last two decades, many rigorous results have been obtained. First runtime analyses of ant colony optimization (ACO) have been conducted only recently. In these studies simple ACO algorithms such as the 1-ANT are investigated. The influence of the evaporation factor in the pheromone update mechanism and the robustness of this parameter w.r.t. the runtime behavior have been determined for the example function OneMax. This work puts forward the rigorous runtime analysis of the 1-ANT on the example functions LeadingOnes and BinVal. With respect to Evolutionary Algorithms (EAs), such analyses were essential to develop methods for the analysis on more complicated problems. The proof techniques required for the 1-ANT, unfortunately, differ significantly from those for EAs, which means that a new reservoir of methods has to be built up. Again, the influence of the evaporation factor is analyzed rigorously, and it is proved that its choice has a crucial impact on the runtime. Moreover, the analyses provide insight into the working principles of ACO algorithms. Our theoretical results are accompanied by experimental results that give us a more detailed impression of the 1-ANT's performance. Furthermore, the experiments also deal with the question whether using many ant solutions in one iteration can decrease the total runtime.