Keywords
Travelling salesman problemAnt colony optimization algorithmsComputer scienceMathematical optimizationSimulated annealingCombinatorial optimizationExtremal optimizationProbabilistic logicStochastic optimizationConvergence (economics)Optimization problemAlgorithmArtificial intelligenceMathematicsMeta-optimization
Affiliated Institutions
Related Publications
Ant system: optimization by a colony of cooperating agents
An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach...
Applying the genetic approach to simulated annealing in solving some NP-hard problems
A stochastic approach called the annealing-genetic algorithm is presented for solving some well-known combinatorial optimization problems. This approach incorporates genetic alg...
Ant colony system: a cooperative learning approach to the traveling salesman problem
This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to the traveling salesman problem (TSP). In the ACS, a set of cooperating agents calle...
A new version of ant system for subset problems
Early applications of Ant Colony Optimization (ACO) have been mainly concerned with solving ordering problems (e.g., traveling salesman problem). We introduce a new version of A...
An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem
We present a new local optimizer called SOP-3-exchange for the sequential ordering problem that extends a local search for the traveling salesman problem to handle multiple cons...
Publication Info
- Year
- 2004
- Type
- book-chapter
- Pages
- 238-249
- Citations
- 76
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
76
OpenAlex
Cite This
Walter J. Gutjahr
(2004).
S-ACO: An Ant-Based Approach to Combinatorial Optimization Under Uncertainty.
Lecture notes in computer science
, 238-249.
https://doi.org/10.1007/978-3-540-28646-2_21
Identifiers
- DOI
- 10.1007/978-3-540-28646-2_21