A New Hybrid Simulated Annealing Algorithm for Large Scale Global Optimization

The present paper focus on the improvement of the efficiency of structural optimization, in typical structural optimization problems there may be many locally minimum configurations. For that reason, the application of a global method, which may escape from the locally minimum points, remain essenti...

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Veröffentlicht in:International journal of manufacturing, materials, and mechanical engineering Jg. 5; H. 3; S. 24 - 36
Hauptverfasser: Kadry, Seifedine N, El Hami, Abdelkhalak
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hershey IGI Global 01.07.2015
Schlagworte:
Algorithms
Analysis
Approximation
Computer programs
Constraints
Global optimization
Mathematical analysis
Mathematical models
Optimization
Perturbation
Perturbation methods
Simulated annealing
Simulation
Stochasticity
Structural analysis
Topology
ISSN:2156-1680, 2156-1672
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Zusammenfassung:The present paper focus on the improvement of the efficiency of structural optimization, in typical structural optimization problems there may be many locally minimum configurations. For that reason, the application of a global method, which may escape from the locally minimum points, remain essential. In this paper, a new hybrid simulated annealing algorithm for large scale global optimization problems with constraints is proposed. The authors have developed a stochastic algorithm called SAPSPSA that uses Simulated Annealing algorithm (SA). In addition, the Simultaneous Perturbation Stochastic Approximation method (SPSA) is used to refine the solution. Commonly, structural analysis problems are constrained. For the reason that SPSA method involves penalizing constraints a penalty method is used to design a new method, called Penalty SPSA (PSPSA) method. The combination of both methods (Simulated Annealing algorithm and Penalty Simultaneous Perturbation Stochastic Approximation algorithm) provides a powerful hybrid stochastic optimization method (SAPSPSA), the proposed method is applicable for any problem where the topology of the structure is not fixed. It is simple and capable of handling problems subject to any number of constraints which may not be necessarily linear. Numerical results demonstrate the applicability, accuracy and efficiency of the suggested method for structural optimization. It is found that the best results are obtained by SAPSPSA compared to the results provided by the commercial software ANSYS.
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ISSN:2156-1680
2156-1672
DOI:10.4018/IJMMME.2015070102