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Refined runtime analysis of a basic ant colony optimization algorithm
- Source :
- IEEE Congress on Evolutionary Computation
- Publication Year :
- 2007
- Publisher :
- IEEE, 2007.
-
Abstract
- Neumann and Witt (2006) analyzed the runtime of the basic ant colony optimization (ACO) algorithm 1-Ant on pseudo-Boolean optimization problems. For the problem OneMax they showed how the runtime depends on the evaporation factor. In particular, they proved a phase transition from exponential to polynomial runtime. In this work, we simplify the view on this problem by an appropriate translation of the pheromone model. This results in a profound simplification of the pheromone update rule and, by that, a refinement of the results of Neumann and Witt. In particular, we show how the exponential runtime bound gradually changes to a polynomial bound inside the phase of transition.
- Subjects :
- Polynomial
Mathematical optimization
Optimization problem
Meta-optimization
Computer science
Ant colony optimization algorithms
Computer Science::Neural and Evolutionary Computation
Translation (geometry)
ComputingMethodologies_ARTIFICIALINTELLIGENCE
Exponential function
Factor (programming language)
Pheromone
computer
Metaheuristic
Algorithm
computer.programming_language
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2007 IEEE Congress on Evolutionary Computation
- Accession number :
- edsair.doi...........3adf60f960abe5bb7ee7c0201b262464