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» Ant colony optimization and the minimum cut problem
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GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 3 months ago
On the runtime analysis of the 1-ANT ACO algorithm
The runtime analysis of randomized search heuristics is a growing field where, in the last two decades, many rigorous results have been obtained. These results, however, apply pa...
Benjamin Doerr, Frank Neumann, Dirk Sudholt, Carst...
GECCO
2003
Springer
130views Optimization» more  GECCO 2003»
15 years 2 months ago
Extracting Test Sequences from a Markov Software Usage Model by ACO
The aim of the paper is to investigate methods for deriving a suitable set of test paths for a software system. The design and the possible uses of the software system are modelled...
Karl Doerner, Walter J. Gutjahr
GECCO
2007
Springer
215views Optimization» more  GECCO 2007»
15 years 1 months ago
Finding safety errors with ACO
Model Checking is a well-known and fully automatic technique for checking software properties, usually given as temporal logic formulae on the program variables. Most model checke...
Enrique Alba, J. Francisco Chicano
JGO
2010
121views more  JGO 2010»
14 years 8 months ago
The oracle penalty method
A new and universal penalty method is introduced in this contribution. It is especially intended to be applied in stochastic metaheuristics like genetic algorithms, particle swarm...
Martin Schlüter, Matthias Gerdts
LION
2009
Springer
210views Optimization» more  LION 2009»
15 years 4 months ago
Beam-ACO Based on Stochastic Sampling: A Case Study on the TSP with Time Windows
Beam-ACO algorithms are hybrid methods that combine the metaheuristic ant colony optimization with beam search. They heavily rely on accurate and computationally inexpensive boundi...
Manuel López-Ibáñez, Christia...