Multi-objective optimization design of bridge piers with hybrid heuristic algorithms  

作　　者：Francisco J. MARTINEZ-MARTIN Fernando GONZALEZ-VIDOSA Antonio HOSPITALER Víctor YEPES 

机构地区：[1]Department of Geotechnical Engineering, Universitat Politècnica de València, 46022 Valencia, Spain [2]Department of Construction Engineering, ICITECH, Universitat Politècnica de València, 46022 Valencia, Spain

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2012年第6期420-432,共13页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：supported by the Spanish Ministry of Science and Innovation(No. BIA2011-23602);the European Community with the European Regional Development Fund (FEDER), Spain

摘　　要：This paper describes one approach to the design of reinforced concrete (RC) bridge piers, using a three-hybrid multi- objective simulated annealing (SA) algorithm with a neighborhood move based on the mutation operator from the genetic algorithms (GAs), namely MOSAMO1, MOSAMO2 and MOSAMO3. The procedure is applied to three objective functions: the economic cost, the reinforcing steel congestion and the embedded CO 2 emissions. Additional results for a random walk and a descent local search multi-objective algorithm are presented. The evaluation of solutions follows the Spanish Code for structural concrete. The methodology was applied to a typical bridge pier of 23.97 m in height. This example involved 110 design variables. Results indicate that algorithm MOSAMO2 outperforms other algorithms regarding the definition of Pareto fronts. Further, the proposed procedure will help structural engineers to enhance their bridge pier designs.This paper describes one approach to the design of reinforced concrete （RC） bridge piers, using a three-hybrid multi- objective simulated annealing （SA） algorithm with a neighborhood move based on the mutation operator from the genetic algo- rithms （GAs）, namely MOSAMO1, MOSAMO2 and MOSAMO3. The procedure is applied to three objective functions： the economic cost, the reinforcing steel congestion and the embedded CO2 emissions. Additional results for a random walk and a descent local search multi-objective algorithm are presented. The evaluation of solutions follows the Spanish Code for structural concrete. The methodology was applied to a typical bridge pier of 23.97 m in height. This example involved 110 design variables. Results indicate that algorithm MOSAMO2 outperforms other algorithms regarding the definition of Pareto fronts. Further, the proposed procedure will help structural engineers to enhance their bridge pier designs.

关 键 词：Bridge piers Concrete structures Multi-objective optimization Simulated annealing (SA) Structural design 

分 类 号：U443.22[建筑科学—桥梁与隧道工程]