Аннотация: various metaheuristics, such as method of simulated annealing, are currently used for solving the tasks of resource usage optimization and computation scheduling. Simulated annealing is a serial method and it is difficult to parallelize it. However, different methods of parallelization have been developed recently in order to improve the quality of the solutions and the time of algorithm execution. The subjects of the study are the methods of parallelization for annealing simulation, in particular, the method of independent starts with and without synchronization. As an example of simulated annealing implementation the authors select the method with thermal scheme “quenching” as the fastest one. The article shows analytical review of simulated annealing parallelization, with a selection of the most promising methods, for which a series of computational experiments was carried out. Scientific novelty of the work is in the discovery of new dependencies and trends that were not described previously in similar studies. In discussing the parallelized annealing simulation with synchronization the authors raise a question of the existence of the dependence of the quality of the solutions with not only the number of computing devices, but also with the frequency of the solutions exchanges. For asynchronous parallel simulated annealing the article shows a tendency to solutions improvement with the increase of the number of computing devices, while for synchronous simulated annealing a similar dependence was not found.

Ключевые слова: simulated annealing, parallel algorithm, optimization, computational system, resource optimization, parallel computing, resource assigning, metaheuristics, parallelization techniques, computation scheduling

Библиография:
MsGee A. A. and Markarian M. D. Optimum Allocation of Research (Engineering Manpower within a Multi-Project Organizational Structures). IRE Trans. Engng. Manag., v. 9, No. 3, 1962.
Levy F. E., Thompson G., Wiest J. Multiship, Multishop, Workloadsmoothing Program, Naval Research, Logistics Quarterly, v. 9, No. 1, 1962.
Fey S.F. Least Cost Estimating and Scheduling with Limited Resources. Abstract. Recent Advances Math. Programm, 1963.
Barskiy A.B. Parallel'nye protsessy v vychislitel'nykh sistemakh: planirovanie i organizatsiya. – M.: Radio i svyaz', 1990.
F. Busetti, Simulated annealing overview. 2003. (http://citeseer.uark.edu:8080/citeseerx/viewdoc/summary;jsessionid=9F958F3AD8ACB341A84315A737883592?doi=10.1.1.66.5018)
L.Ingber, Simulated annealing: practice versus theory.1993. (http://citeseer.uark.edu:8080/citeseerx/viewdoc/summary?doi=10.1.1.15.1046)
Crainic T.G., Toulouse M. Parallel Metaheuristics. In T. G. Crainic and G. Laporte, editors, Fleet Management and Logistics, pages 205-25 1, 1998. Kluwer Academic Publishers.

References (transliteration):
MsGee A. A. and Markarian M. D. Optimum Allocation of Research (Engineering Manpower within a Multi-Project Organizational Structures). IRE Trans. Engng. Manag., v. 9, No. 3, 1962.
Levy F. E., Thompson G., Wiest J. Multiship, Multishop, Workloadsmoothing Program, Naval Research, Logistics Quarterly, v. 9, No. 1, 1962.
Fey S.F. Least Cost Estimating and Scheduling with Limited Resources. Abstract. Recent Advances Math. Programm, 1963.
Barskiy A.B. Parallel'nye protsessy v vychislitel'nykh sistemakh: planirovanie i organizatsiya. – M.: Radio i svyaz', 1990.
F. Busetti, Simulated annealing overview. 2003. (http://citeseer.uark.edu:8080/citeseerx/viewdoc/summary;jsessionid=9F958F3AD8ACB341A84315A737883592?doi=10.1.1.66.5018)
L.Ingber, Simulated annealing: practice versus theory.1993. (http://citeseer.uark.edu:8080/citeseerx/viewdoc/summary?doi=10.1.1.15.1046)
Crainic T.G., Toulouse M. Parallel Metaheuristics. In T. G. Crainic and G. Laporte, editors, Fleet Management and Logistics, pages 205-25 1, 1998. Kluwer Academic Publishers.

Аннотация: the article deals with the problem of decomposition of simulation models for organization of the distributed modelling of complex systems on multiprocessor computing systems. To speed up the process of modelling the modelling program shall be divided into parts for parallel execution on different processors. The author offers the approach to the use of an automatic classification method for automation the parallelization of simulation programs.

Ключевые слова: Software, simulation modeling, complex systems, multi-processor computing systems, decomposition of simulation model, automatic classification, distributed modeling, acceleration of computation, parallel computing, modeling programs.

Контактная информация: Olzoeva Seseg Ivanovna, 670013, Russia, Republic of Buryatiya, Ulan-Ude, ul. Smolina, d. 25.

Библиография:
1. Emel'yanov V.V., Yasinovskiy S.I. Vvedenie v intellektual'noe imitatsionnoe modelirovanie
slozhnykh diskretnykh sistem i protsessov. Yazyki RDO. — M.: ANVIK, 1998, — 427 s.
2. Olzoeva S.I. Raspredelennoe modelirovanie v zadachakh razrabotki ASU. – Ulan-Ude: Izd-vo VSGTU,
2005, — 219 s.

References (transliteration):
1. Emel'yanov V.V., Yasinovskiy S.I. Vvedenie v intellektual'noe imitatsionnoe modelirovanie
slozhnykh diskretnykh sistem i protsessov. Yazyki RDO. — M.: ANVIK, 1998, — 427 s.
2. Olzoeva S.I. Raspredelennoe modelirovanie v zadachakh razrabotki ASU. – Ulan-Ude: Izd-vo VSGTU,
2005, — 219 s.