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Cites:

1

Information Journal Paper

Title

A COMPARATIVE STUDY OF TWO META-HEURISTIC ALGORITHMS FOR OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMES

Pages

  193-206

Abstract

 This article presents the application of two algorithms: heuristic big bang-big crunch (HBB-BC) and a heuristic PARTICLE SWARM ANT COLONY OPTIMIZATION (HPSACO) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on ACI 318-08 code. The objective function is the total cost of the frame which includes the cost of concrete, formwork and reinforcing steel for all members of the frame. The heuristic big bang-big crunch (HBB-BC) is based on BB-BC and a harmony search (HS) scheme to deal with the variable constraints. The HPSACO algorithm is a combination of PARTICLE SWARM with passive congregation (PSOPC), ANT COLONY OPTIMIZATION (ACO), and harmony search scheme (HS) algorithms. In this paper, by using the capacity of BB-BC in ACO stage of HPSACO, its performance is improved. Some design examples are tested using these methods and the results are compared.

Cites

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  • Cite

    APA: Copy

    KAVEH, ALI, & SABZI, OMID. (2011). A COMPARATIVE STUDY OF TWO META-HEURISTIC ALGORITHMS FOR OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMES. INTERNATIONAL JOURNAL OF CIVIL ENGINEERING, 9(3), 193-206. SID. https://sid.ir/paper/271877/en

    Vancouver: Copy

    KAVEH ALI, SABZI OMID. A COMPARATIVE STUDY OF TWO META-HEURISTIC ALGORITHMS FOR OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMES. INTERNATIONAL JOURNAL OF CIVIL ENGINEERING[Internet]. 2011;9(3):193-206. Available from: https://sid.ir/paper/271877/en

    IEEE: Copy

    ALI KAVEH, and OMID SABZI, “A COMPARATIVE STUDY OF TWO META-HEURISTIC ALGORITHMS FOR OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMES,” INTERNATIONAL JOURNAL OF CIVIL ENGINEERING, vol. 9, no. 3, pp. 193–206, 2011, [Online]. Available: https://sid.ir/paper/271877/en

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