A New Hybrid Simulated Annealing Algorithm for Large Scale Global Optimization

• Published in: International journal of manufacturing, materials, and mechanical engineering Vol. 5; no. 3; pp. 24 - 36
• Main Authors: Kadry, Seifedine N, El Hami, Abdelkhalak
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.07.2015
• Subjects: 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
• DOI: 10.4018/IJMMME.2015070102

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.