Paper Info
Title
Multi-core implementation of the differential ant-stigmergy algorithm for numerical optimization
Abstract
Numerical optimization techniques are applied to a variety of engineering problems. The cost-function evaluation is an important part of any numerical optimization and is usually realized as a black-box simulator. For the efficient solving of the numerical optimization problem on multi-core systems, new shared-memory and distributed-memory approaches are proposed. The algorithms are based on an ant-stigmergy meta-heuristics, where indirect coordination between the ants drives the search procedure toward the optimal solution. Indirect coordination offers a high degree of parallelism and therefore relatively straightforward shared-memory and distributed-memory implementations. The Intel-OpenMP 3.0 and MPICH2 libraries are used for the inter-thread and inter-process communications, respectively. It is shown that speed-up strongly depends on the simulation time. This is especially evident in a distributed-memory implementation. Therefore, the algorithms' performances, according to the simulator's time complexity, are experimentally evaluated and discussed.
Year
DOI
Venue
2013
10.1007/s11227-012-0772-z
The Journal of Supercomputing
Keywords
Field
DocType
Numerical optimization,Differential ant-stigmergy algorithm,Parallelization,Multi-core processor
Degree of parallelism,Computer science,Time complexity,Stigmergy,Multi-core processor,Optimization problem,Distributed computing,Metaheuristic,Mathematical optimization,Meta-optimization,Parallel computing,Algorithm,Multi-swarm optimization
Journal
Volume
Issue
ISSN
63
3
0920-8542
Citations 
PageRank 
References 
0
0.34
18
Authors
4
Name
Order
Citations
PageRank
Peter Korošec115317.80
Marian Vajteršic242.41
Jurij Šilc322019.94
Rade Kutil4618.80