DocumentCode :
2530726
Title :
PARMETAOPT — Parallel metaheuristics framework for combinatorial optimization problems
Author :
Borovska, Plamenka ; Nakov, Ognian ; Lazarova, Milena
Author_Institution :
Dept. of Comput. Syst., Tech. Univ. of Sofia, Sofia, Bulgaria
fYear :
2009
fDate :
21-23 Sept. 2009
Firstpage :
225
Lastpage :
230
Abstract :
The paper presents an experimental parallel metaheuristics framework for solving combinatorial optimization of grand challenge scientific and engineering problems that has been developed based on biologically inspired metaheuristics, modeling of social behavior and cultural evolution as well as trajectory-based methods. A prototype class library for metaheuristics is developed and several parallel computational models of metaheuristics for solving combinatorial optimization problems are implemented. The library contains implementations in C++ of parallel computational models for both population based and trajectory based metaheuristics. Some improvements in the parallel models are suggested and implemented in the library PARMETAOPT. The influence of the parameters on the performance of some of the parallel algorithms is analyzed using the developed parallel metaheuristics framework and performance tuning rules are suggested. The implementations are based on message passing with MPICH2 for the flat programming models and OpenMP API is used for multithreading in the hybrid programming models.
Keywords :
combinatorial mathematics; mathematics computing; optimisation; parallel algorithms; C++; MPICH2; OpenMP API; PARMETAOPT; biologically inspired metaheuristics; combinatorial optimization problems; flat programming models; hybrid programming models; message passing; multithreading; parallel algorithms; parallel computational models; parallel metaheuristics framework; prototype class library; social behavior modeling; trajectory-based methods; Biological system modeling; Biology computing; Computational modeling; Concurrent computing; Cultural differences; Design engineering; Evolution (biology); Libraries; Optimization methods; Prototypes; message passing; metaheuristics class libraries; multithreading; near-optimal solution; optimization problems; parallel computational model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2009. IDAACS 2009. IEEE International Workshop on
Conference_Location :
Rende
Print_ISBN :
978-1-4244-4901-9
Electronic_ISBN :
978-1-4244-4882-1
Type :
conf
DOI :
10.1109/IDAACS.2009.5342991
Filename :
5342991
Link To Document :
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