Recently, the first rigorous runtime analyses of ACO algorithms appeared, covering variants of the MAX - MIN ant system and their runtime on pseudo-Boolean functions. Interestingly, a variant called 1-ANT is very sensitive to the evaporation factor while Gutjahr and Sebastiani proved partly opposite results for their variant MMASbs. These algorithms differ in their pheromone update mechanisms and, moreover, 1-ANT accepts equally fit solutions in contrast to MMASbs. By analyzing variants of MMASbs, we prove that the different behavior of 1-ANT and MMASbs results from the different pheromone update mechanisms. Building upon results by Gutjahr and Sebastiani, we extend their analyses of MMASbs to the class of unimodal functions and show improv...
We undertake a rigorous experimental analysis of the optimization behavior of the two most studied ...
Ant colony optimization (ACO) is a kind of randomized search heuristic method for solving NP-hard pr...
AbstractThe runtime analysis of randomized search heuristics is a growing field where, in the last t...
Recently, the first rigorous runtime analyses of ACO algorithms appeared, covering variants of the M...
Also published as a journal article: Lecture Notes in Computer Science, 2007; 4638:61-75Recently, th...
Recently, the first rigorous runtime analyses of ACO algorithms have been presented. These results c...
With this paper, we contribute to the understanding of ant colony optimization (ACO) algorithms by f...
Neumann and Witt (2006) analyzed the runtime of the basic ant colony optimization (ACO) algorithm {\...
Ant colony optimization (ACO) is a promising meta-heuristic and a great amount of research has been ...
Ant colony optimization (ACO) is a promising metaheuristic and a great amount of research has been d...
We undertake a rigorous experimental analysis of the optimization behavior of the two most studied s...
Ant colony optimization (ACO) has found many applications in different problem domains. We carry out...
Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization pro...
n this paper, we introduce the MAF-ACO algorithm, which emulates the foraging behavior of ants found...
Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization pro...
We undertake a rigorous experimental analysis of the optimization behavior of the two most studied ...
Ant colony optimization (ACO) is a kind of randomized search heuristic method for solving NP-hard pr...
AbstractThe runtime analysis of randomized search heuristics is a growing field where, in the last t...
Recently, the first rigorous runtime analyses of ACO algorithms appeared, covering variants of the M...
Also published as a journal article: Lecture Notes in Computer Science, 2007; 4638:61-75Recently, th...
Recently, the first rigorous runtime analyses of ACO algorithms have been presented. These results c...
With this paper, we contribute to the understanding of ant colony optimization (ACO) algorithms by f...
Neumann and Witt (2006) analyzed the runtime of the basic ant colony optimization (ACO) algorithm {\...
Ant colony optimization (ACO) is a promising meta-heuristic and a great amount of research has been ...
Ant colony optimization (ACO) is a promising metaheuristic and a great amount of research has been d...
We undertake a rigorous experimental analysis of the optimization behavior of the two most studied s...
Ant colony optimization (ACO) has found many applications in different problem domains. We carry out...
Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization pro...
n this paper, we introduce the MAF-ACO algorithm, which emulates the foraging behavior of ants found...
Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization pro...
We undertake a rigorous experimental analysis of the optimization behavior of the two most studied ...
Ant colony optimization (ACO) is a kind of randomized search heuristic method for solving NP-hard pr...
AbstractThe runtime analysis of randomized search heuristics is a growing field where, in the last t...