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Engineering with Computers
Erschienen in: Engineering with Computers 4/2017

04.04.2017 | Original Article

Multi-objective seismic design optimization of steel frames by a chaotic meta-heuristic algorithm

verfasst von: Saeed Gholizadeh, Amir Baghchevan

Erschienen in: Engineering with Computers | Ausgabe 4/2017

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Abstract

In this study, multi-objective optimization is applied to implement performance-based design of steel moment-resisting frame (SMRF) structures. In order to efficiently achieve this purpose, a chaotic multi-objective firefly algorithm (CMOFA) is proposed to find the Pareto optimal front for the multi-objective performance-based optimum design (MO-PBOD) problem of SMRFs. The structural weight and the maximum inter-story drift at performance levels are taken as the conflicting objective functions of the MO-PBOD problem which should be optimized simultaneously subject to serviceability and ultimate limit-state constraints. In order to illustrate the efficiency of the proposed CMOFA meta-heuristic, two benchmark truss examples and three MO-PBOD examples of SMRFs are presented. The numerical results demonstrate the better computational performance of the proposed CMOFA meta-heuristic in comparison with some existing multi-objective algorithms.
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Literatur
1.
FEMA-356 (2000) Prestandard and commentary for the seismic rehabilitation of buildings. Federal Emergency Management Agency, Washington
2.
Gholizadeh S (2015) Performance-based optimum seismic design of steel structures by a modified firefly algorithm and a new neural network. Adv Eng Softw 81:50–65CrossRef
3.
Gholizadeh S (2013) Layout optimization of truss structures by hybridizing cellular automata and particle swarm optimization. Comput Struct 125:86–99CrossRef
4.
Gandomi AH, Talatahari S, Yang XS, Deb S (2012) Design optimization of truss structures using cuckoo search algorithm. Struct Des Tall Spec Build 22:1330–1349CrossRef
5.
Yang XS (2009) Firefly algorithms for multimodal optimization. In: Watanabe O, Zeugmann T (eds) Stochastic algorithms: foundations and applications. SAGA 2009, Lecture Notes in Computer Science, 5792. Springer, Berlin, pp 169–178CrossRef
6.
Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6:182–197CrossRef
7.
Coello CAC, Pulido GT, Lechuga MS (2004) Handling multiple objectives with particle swarm optimization. IEEE Trans Evol Comput 8:256–279CrossRef
8.
Kaveh A, Laknejadi K (2013) A new multi-swarm multi-objective optimization method for structural design. Adv Eng Softw 58:54–69CrossRefMATH
9.
Yang XS, Karamanoglu M, He X (2014) Flower pollination algorithm: a novel approach for multiobjective optimization. Eng Optim 46:1222–1237MathSciNetCrossRef
10.
Gholizadeh S, Milani A (2016) Optimal performance-based design of steel frames using advanced metaheuristics. Asian J Civ Eng 17:607–623
11.
Papadrakakis M, Lagaros ND, Plevris V (2002) Multi-objective optimization of skeletal structures under static and seismic loading conditions. Eng Optim 34:645–669CrossRefMATH
12.
Liu M, Burns SA, Wen YK (2005) Multiobjective optimization for performance-based seismic design of steel moment frame structures. Earthq Eng Struct Dyn 34:289–306CrossRef
13.
Fragiadakis M, Lagaros ND, Papadrakakis M (2006) Performance-based multiobjective optimum design of steel structures considering life-cycle cost. Struct Multidisc Optim 32:1–11CrossRef
14.
Saadat S, Camp CV, Pezeshk S (2014) Seismic performance-based design optimization considering direct economic loss and direct social loss. Eng Struct 76:193–201CrossRef
15.
16.
17.
Talatahari S, Sheikholeslami R, Farahmand Azar B, Gandomi AH (2012) Imperialist competitive algorithm combined with chaos for global optimization. Commun Nonlinear Sci Numer Simul 17:1312–1319MathSciNetCrossRefMATH
18.
Gandomi AH, Yun GJ, Yang XS, Talatahari S (2013) Chaos-enhanced accelerated particle swarm optimization. Commun Nonlinear Sci Numer Simul 18:327–340MathSciNetCrossRefMATH
19.
20.
Wang GG, Deb S, Gandomi AH, Zhang Z, Alavi AH (2016) Chaotic cuckoo search. Soft Comput 20:3349–3362CrossRef
21.
Gholizadeh S, Poorhoseini H (2016) Seismic layout optimization of steel braced frames by an improved dolphin echolocation algorithm. Struct Multidisc Optim 54:1011–1029.CrossRef
22.
FEMA P-58-1 (2012) Seismic performance assessment of buildings. Federal Emergency Management Agency, Washington
23.
Mazzoni S, Mckenna F, Fenves GL (2006) OpenSees command language manual. Pacific Earthquake Engineering Research (PEER) Center, Berkeley
24.
LRFD-AISC (2001) Manual of steel construction. Load and resistance factor design. American Institute of Steel Construction, Chicago
25.
Hasancebi O, Bahcecioglu T, Kurc O, Saka MP (2011) Optimum design of high-rise steel buildings using an evolution strategy integrated parallel algorithm. Comput Struct 89:2037–2051CrossRef
26.
Gholizadeh S, Fattahi F (2014) Design optimization of tall steel buildings by a modified particle swarm algorithm. Struct Des Tall Spec Build 23:285–301CrossRef
27.
Coello CAC, Van Veldhuizen DA, Lamont GB (2002) Evolutionary algorithms for solving multi-objective problems. Kluwer Academic Publishers, New YorkCrossRefMATH
28.
Yang XS (2013) Multiobjective firefly algorithm for continuous optimization. Eng Comput 29:175–184CrossRef
29.
Lin JH, Chou CW, Yang CH, Tsai HL (2012) A chaotic Levy flight bat algorithm for parameter estimation in nonlinear dynamic biological systems. J Comput Inf Tech 2:56–63
30.
31.
Chen G, Liu L, Song P, Du Y (2014) Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems. Energy Convers Manag 86:548–560CrossRef
32.
Pana I, Das S (2015) Fractional-order load-frequency control of interconnected power systems using chaotic multi-objective optimization. Appl Soft Comput 29:328–344CrossRef
33.
He D, He C, Jiang L, Zhu H, Hu G (2001) Chaotic characteristic of a one-dimensional iterative map with infinite collapses. IEEE Circuits Syst 48: 900–906MathSciNetCrossRefMATH
34.
Li Y, Deng S, Xiao D (2011) A novel Hash algorithm construction based on chaotic neural network. Neural Comput Appl 20:133–141CrossRef
35.
36.
Zitzler E, Deb K, Thiele L (2000) Comparison of multi-objective evolutionary algorithms: empirical results. Evol Comput 8:173–195CrossRef
37.
HAZUS-MH MR1 (2003) Multi-hazard Loss estimation methodology earthquake model. FEMA-National Institute of Building Sciences, Washington
Metadaten
Titel
Multi-objective seismic design optimization of steel frames by a chaotic meta-heuristic algorithm
verfasst von
Saeed Gholizadeh
Amir Baghchevan
Publikationsdatum
04.04.2017
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 4/2017
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-017-0515-0

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