Sizing optimization of truss structures with discrete design variables using combined PSO algorithm with Special Particles Method
Subject Areas : Design of ExperimentAli Gheibi 1 , Reza SojoudiZadeh 2 , Hadi Azizian 3 , Mahdi Gheibi 4
1 -
2 -
3 -
4 -
Keywords: PSO, Discrete optimization, Truss structures, Metaheuristic, Sizing optimization,
Abstract :
This paper proposes a modified particle swarm optimization (MPSO) algorithm for discrete sizing optimization of truss structures. The original particle swarm optimization (PSO) is a population-based metaheuristic that fluctuates the search agents about the best solution based on Eberhart functions. The efficiency of the PSO in solving standard optimization problems of well-known problems of truss structures has been demonstrated in literature. However, its performance in tackling the discrete optimization problems of truss structures is not competitive compared with the recent existing metaheuristic algorithms. In the framework of the proposed MPSO a number of worst solutions of the current population is replaced by some variants of the global best solution found so far. Moreover, an efficient mutation operator is added to the algorithm that reduces the probability of getting stuck in local optima. The efficiency of the proposed MPSO is illustrated through two benchmark optimization problems of truss structures.
Cheng MY, Prayogo D, Wu YW, Lukito MM. (2016).A hybrid harmony search algorithm for discrete sizing optimization of truss structure. Automat Constr; 69: 21-33.
Dorigo M, Birattari M. (2010).Ant colony optimization, Encyclopedia of Machine Learning, Springer, pp. 36–39.
Eberhart RC, Kennedy J. (1995).A new optimizer using particle swarm theory, in: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp. 39–43.
Gholizadeh S, Ebadijalal M. (2018).Performance based discrete topology optimization of steel braced frames by a new metaheuristic. Adv Eng Softw, 123: 77–92.
Gholizadeh S, Milany A. (2018).An improved fireworks algorithm for discrete sizing optimization of steel skeletal structures. Eng Optim. doi.org/10.1080/0305215X.2017.1417402.
Gholizadeh S, Poorhoseini H. (2016). Seismic layout optimization of steel braced frames by an improved dolphin echolocation algorithm. Struct Multidisc Optim, 54:1011–29..
Gholizadeh S.(2013). Layout optimization of truss structures by hybridizing cellular automata and particle swarm optimization. Comput Struct, 125: 86-99.
Ho-Huu V, Nguyen-Thoi T, Vo-Duy T, Nguyen-Trang T.(2016). An adaptive elitist differential evolution for optimization of truss structures with discrete design variables. Comput Struct 2016; 165: 59-75.
Holland J,Reitman J.Cognitive (1997). Systems based on adaptive algorithms, AC SIGART Bull 1977;63:49–49.
Kaveh A, Farhoudi N.A (2013).New optimization method: Dolphin echolocation.Adv Eng Softw, 59:53–70.
Kaveh A, Ilchi Ghazaan M. (2015).A comparative study of CBO and ECBO for optimal design of skeletal structures. Comput Struct, 153:137-47.
Kaveh A, Mahdavi VR.(2014). Colliding Bodies Optimization method for optimum discrete design of truss structures, Comput Struct, 139: 43–53.
Kaveh A, Talatahari S. (2009a).A particle swarm ant colony optimization for truss structures with discrete variables. J Constr Steel Res, 65:1558-68.
Kaveh A, Talatahari S.(2009b) Size optimization of space trusses using Big Bang-Big Crunch algorithm. Comput Struct, 87:1129-40.
Li LJ, Huang ZB, Liu F.(2009). A heuristic particle swarm optimization method for truss structures with discrete variables. Comput Struct, 87:435-43.
Mirjalili S. SCA: A Sine Cosine Algorithm for solving optimization problems, Knowl-Based Syst 2016; 96: 120-133.
Rashedi E, Nezamabadi-Pour H, Saryazdi S. (2009).GSA: a gravitational search algorithm. Inf Sci, 179: 2232–2248.
Sadollah A, Eskandar H, Bahreininejad A, Kim JH. (2015).Water cycle, mine blast and improved mine blast algorithms for discrete sizing optimization of truss structures. Comput Struct, 149:1-16.
Simon D. (2008).Biogeography-based optimization, IEEE Trans Evol Comput,12: 702–713.
Storn R, Price K. (1997).Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim, 11: 341–359.
Yang XS. (2010).A new metaheuristic bat-inspired algorithm. Nature inspired cooperative strategies for optimization,studies in computational intelligence, J. R.Gonzalez, ed., Vol. 284, Springer, Berlin, 65–74.
Zhu JH, He F, Liu T, FH, Zhang WH, Liu Q, Yang C. (2018).Structural topology optimization under harmonic base acceleration excitations. Struct Multidiscip Optim, 57: 1061-1078.