Parallel Computations on Reconfigurable Meshes
IEEE Transactions on Computers
Integer summing algorithms on reconfigurable meshes
Theoretical Computer Science
The ant colony optimization meta-heuristic
New ideas in optimization
ACO algorithms for the quadratic assignment problem
New ideas in optimization
An ACO algorithm for the shortest common supersequence problem
New ideas in optimization
Future Generation Computer Systems
Journal of Heuristics
The Ant System Applied to the Quadratic Assignment Problem
IEEE Transactions on Knowledge and Data Engineering
Bit Summation on the Reconfigurable Mesh
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Exact and Approximate Nondeterministic Tree-Search Procedures for the Quadratic Assignment Problem
INFORMS Journal on Computing
An Iterated Dynasearch Algorithm for the Single-Machine Total Weighted Tardiness Scheduling Problem
INFORMS Journal on Computing
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
The Journal of Supercomputing
Hardware-oriented ant colony optimization
Journal of Systems Architecture: the EUROMICRO Journal
High speed ant colony optimization CMOS chip
Expert Systems with Applications: An International Journal
A survey on parallel ant colony optimization
Applied Soft Computing
Adaptive parallel ant colony algorithm
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Adaptive parallel ant colony optimization
ISPA'05 Proceedings of the Third international conference on Parallel and Distributed Processing and Applications
An improved parallel ant colony optimization based on message passing interface
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Counter-Based ant colony optimization as a hardware-oriented meta-heuristic
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Information Sciences: an International Journal
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Ant Colony Optimization (ACO) is a metaheuristic used to solve combinatorial optimization problems. As with other metaheuristics, like evolutionary methods, ACO algorithms often show good optimization behavior but are slow when compared to classical heuristics. Hence, there is a need to find fast implementations for ACO algorithms. In order to allow a fast parallel implementation, we propose several changes to a standard form of ACO algorithms. The main new features are the non-generational approach and the use of a threshold based decision function for the ants. We show that the new algorithm has a good optimization behavior and also allows a fast implementation on reconfigurable processor arrays. This is the first implementation of the ACO approach on a reconfigurable architecture. The running time of the algorithm is quasi-linear in the problem size n and the number of ants on a reconfigurable mesh with n2 processors, each provided with only a constant number of memory words.