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2017 | OriginalPaper | Chapter

20. Multi-Objective Optimization of Truss Structures

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Abstract

In this chapter a multi-objective optimization (MOP) is presented that uses the main concepts of charged system search algorithm (Kaveh and Massoudi [1]).

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Literature
1.
go back to reference Kaveh A, Massoudi MS (2014) Multi-objective optimization using charged system search. Scientia Iranica 21(6):1845–1860 Kaveh A, Massoudi MS (2014) Multi-objective optimization using charged system search. Scientia Iranica 21(6):1845–1860
2.
go back to reference Dorigo M, Maniezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern 26:29–41CrossRef Dorigo M, Maniezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern 26:29–41CrossRef
3.
go back to reference Erol OK, Eksin I (2006) New optimization method: Big Bang–Big Crunch. Adv Eng Softw 37:106–111CrossRef Erol OK, Eksin I (2006) New optimization method: Big Bang–Big Crunch. Adv Eng Softw 37:106–111CrossRef
4.
go back to reference Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781–798CrossRef Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781–798CrossRef
5.
go back to reference Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213:267–289CrossRefMATH Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213:267–289CrossRefMATH
6.
go back to reference Kaveh A, Khayatazad M (2012) A new metaheuristic method: ray optimization. Comput Struct 112–113:283–294CrossRef Kaveh A, Khayatazad M (2012) A new metaheuristic method: ray optimization. Comput Struct 112–113:283–294CrossRef
7.
go back to reference Kaveh A, Farhoudi N (2013) A new optimization method: dolphin echolocation. Adv Eng Softw 59:53–70CrossRef Kaveh A, Farhoudi N (2013) A new optimization method: dolphin echolocation. Adv Eng Softw 59:53–70CrossRef
8.
go back to reference Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6:182–197CrossRef Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6:182–197CrossRef
9.
go back to reference Zitzler E, Laumanns M, Thiele L (2001) SPEA2: improving the strength Pareto evolutionary algorithm. Swiss Federal Institute Technology, Zurich Zitzler E, Laumanns M, Thiele L (2001) SPEA2: improving the strength Pareto evolutionary algorithm. Swiss Federal Institute Technology, Zurich
10.
go back to reference Knowles JD, Corne DW (2000) Approximating the non-dominated front using the Pareto archived evolution strategy. Evol Comput 8:149–172CrossRef Knowles JD, Corne DW (2000) Approximating the non-dominated front using the Pareto archived evolution strategy. Evol Comput 8:149–172CrossRef
11.
go back to reference Coello Coello C, Lechuga M (2002) MOPSO: a proposal for multiple objective particle swarm optimization. Proc Congr Evol Comput 1:1051–1056 Coello Coello C, Lechuga M (2002) MOPSO: a proposal for multiple objective particle swarm optimization. Proc Congr Evol Comput 1:1051–1056
12.
go back to reference Kaveh A, Laknejadi K (2011) A hybrid multi-objective optimization and decision making procedure for optimal design of truss structures. Iran J Sci Technol Trans Civil Eng 35:137–154 Kaveh A, Laknejadi K (2011) A hybrid multi-objective optimization and decision making procedure for optimal design of truss structures. Iran J Sci Technol Trans Civil Eng 35:137–154
13.
go back to reference Kaveh A, Talatahari S (2012) Charged system search for optimal design of planar frame structures. Appl Soft Comput 12:382–393CrossRef Kaveh A, Talatahari S (2012) Charged system search for optimal design of planar frame structures. Appl Soft Comput 12:382–393CrossRef
14.
go back to reference Deb K (2001) Multi objective optimization using evolutionary algorithms. Wiley, ChichesterMATH Deb K (2001) Multi objective optimization using evolutionary algorithms. Wiley, ChichesterMATH
15.
go back to reference Kaveh A, Talatahari S (2009) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Comput Struct 87(5–6):267–283CrossRef Kaveh A, Talatahari S (2009) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Comput Struct 87(5–6):267–283CrossRef
16.
go back to reference Mostaghim S, Teich J (2003) Strategies for finding good local guides in multi objective particle swarm optimization (MOPSO). In: Proceedings of the IEEE swarm intelligence symposium, pp 26–33 Mostaghim S, Teich J (2003) Strategies for finding good local guides in multi objective particle swarm optimization (MOPSO). In: Proceedings of the IEEE swarm intelligence symposium, pp 26–33
17.
go back to reference Fishburn PC (1970) Utility theory for decision making. Wiley, New YorkMATH Fishburn PC (1970) Utility theory for decision making. Wiley, New YorkMATH
18.
go back to reference Parreiras RO, Maciel JHRD, Vasconcelos JA (2005) Decision making in multi-objective optimization problems. ISE book series on real word multi-objective system engineering. pp 29–52 Parreiras RO, Maciel JHRD, Vasconcelos JA (2005) Decision making in multi-objective optimization problems. ISE book series on real word multi-objective system engineering. pp 29–52
19.
go back to reference Palli N, Azram S, McCluskey P, Sundararajan R (1999) An interactive multistage є-inequality constraint method for multiple objectives decision making. ASME J Mech Des 4:678–686 Palli N, Azram S, McCluskey P, Sundararajan R (1999) An interactive multistage є-inequality constraint method for multiple objectives decision making. ASME J Mech Des 4:678–686
20.
go back to reference Janga Reddy M, Nagesh Kumar D (2007) An efficient multi-objective optimization algorithm based on swarm intelligence for engineering design. Eng Optim 39:49–68MathSciNetCrossRef Janga Reddy M, Nagesh Kumar D (2007) An efficient multi-objective optimization algorithm based on swarm intelligence for engineering design. Eng Optim 39:49–68MathSciNetCrossRef
21.
go back to reference El-Santawy MF, Ahmed AN (2012) A multi-objective chaotic harmony search for structural optimization. Int J Comput Sci 3:33–39 El-Santawy MF, Ahmed AN (2012) A multi-objective chaotic harmony search for structural optimization. Int J Comput Sci 3:33–39
22.
go back to reference Kelesoglu O (2007) Fuzzy multi-objective optimization of truss-structures using genetic algorithm. Adv Eng Softw 38:717–721CrossRef Kelesoglu O (2007) Fuzzy multi-objective optimization of truss-structures using genetic algorithm. Adv Eng Softw 38:717–721CrossRef
Metadata
Title
Multi-Objective Optimization of Truss Structures
Author
A. Kaveh
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-46173-1_20

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