Implementing Parallel Metaheuristic Optimization Framework Using Metaprogramming and Design Patterns

Andrey V. Tsyganov; Oleg I. Bulychov

doi:10.4028/www.scientific.net/AMM.263-266.1864

Paper Titles

Algorithms of Data Mining and Knowledge Discovery of Correlativity in Two-Dimensional Time Series
p.1844

Design and Implementation of Landscape System for East and West Huashi Street in Beijing Based on Virtual Reality Technology
p.1849

Design and Implementation of Point Symbol Database Based on ArcGIS Engine
p.1853

Experimental Research on Diffserv-Aware MPLS Traffic Engineering
p.1858

Implementing Parallel Metaheuristic Optimization Framework Using Metaprogramming and Design Patterns
p.1864

Minimum Test Case for Discrete-Type Software Reliability Testing by Stratified Sampling
p.1874

Numerical Simulation Study on Longitudinal Aerodynamic Characteristics of a Forward-Swept Wing Air Vehicle
p.1880

Program Slicing Technique in Programming Assessment
p.1884

Research of Disk Operating Technique in UEFI Shell Environment
p.1888

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266Implementing Parallel Metaheuristic Optimization...

Implementing Parallel Metaheuristic Optimization Framework Using Metaprogramming and Design Patterns

Abstract:

In the present paper we introduce an approach to implementing parallel metaheuristic optimization frameworks which is used in the design of the framework HeO. This experimental cross-platform framework is a collection of popular optimization methods implemented in C++ as algorithmic skeletons. The key feature of the discussed approach is the wide usage of metaprogramming and design patterns which allow to increase the reusability of the code and ease the process of hybrid algorithms construction for the end-user. We consider framework structure and implementation details and provide the results of numerical experiments for some well-known optimization problems.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

1864-1873

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.1864

Citation:

Cite this paper

Online since:

December 2012

Authors:

Andrey V. Tsyganov, Oleg I. Bulychov

Keywords:

Design Patterns, Meta-Heuristic, Metaprogramming, Optimization Frameworks, Parallelism

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] E. Alba, G. Luque, J. García-Nieto, G. Ordóñez, and G. Leguizamón: MALLBA: a software library to design efficient optimisation algorithms, Int. J. Innov. Comput. Appl., vol. 1, p.74–85, April 2007.

DOI: 10.1504/ijica.2007.013403

Google Scholar

[2] S. Cahon, N. Melab, and E.-G. Talbi: ParadisEO: a framework for the reusable design of parallel and distributed metaheuristics, Journal of Heuristics, vol. 10, p.357–380, 2004.

DOI: 10.1023/b:heur.0000026900.92269.ec

Google Scholar

[3] D. White: Software review: the ECJ toolkit: Genetic Programming and Evolvable Machines, vol. 13, p.65–67, 2012, 10.1007/s10710-011-9148-z. [Online]. Available:

DOI: 10.1007/s10710-011-9148-z

Google Scholar

[4] S. Wagner: Heuristic optimization software systems — modeling of heuristic optimization algorithms in the HeuristicLab software environment, Ph.D. dissertation, Institute for Formal Models and Verification, Johannes Kepler University Linz, Austria, 2009.

Google Scholar

[5] J. Parejo, A. Ruiz-Cortés, S. Lozano, and P. Fernandez: Metaheuristic optimization frameworks: a survey and benchmarking, Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol. 16, p.527–561, 2012, 10.1007/s00500-011-0754-8. [Online]. Available:

DOI: 10.1007/s00500-011-0754-8

Google Scholar

[6] J. Hromkovič: Algorithmics for Hard Problems: Introduction to Combinatorial Optimization, Randomization, Approximation, and Heuristics. Berlin, Heidelberg: Springer-Verlag, 2010.

DOI: 10.1145/882116.882121

Google Scholar

[7] T. Kameda and P. Weiner: On the state minimization of nondeterministic finite automata, IEEE Transactions on Computers, vol. 19, p.617–627, 1970.

DOI: 10.1109/t-c.1970.222994

Google Scholar

[8] E. Gamma, R. Helm, R. Johnson, and J. Vlissides: Design patterns: elements of reusable object-oriented software. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc., 1995.

Google Scholar