Chaotic biogeography algorithm for size and shape optimization of truss structures with frequency constraints

Abstract

Abstract

Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights

“…The BBO algorithm was first developed by Simon (2008), who adopted the theory of island biogeography. Since its emergence, the BBO algorithm has been applied to many engineering design optimization problems, such as truss structures (Jalill, Hosseinzadeh, and Kaveh 2014), soft-sensor models (Wang et al 2015), AC transmission system devices (Roy, Ghoshal, and Thakur 2011), steel frames (Çarbaş 2016) and cold-formed structures (Saka et al 2015). However, its application to the optimum design of the RC cantilever retaining wall problem is not found in the current literature, other than a conference study which is related to the optimum carbon dioxide emissions of the RC retaining wall design (Aydogdu and Akin 2015).…”

“…Sinha et al (2012) used hybridization of the BBO and ant colony optimization algorithms to resolve mixed pixels. Jalill, Hosseinzadeh, and Kaveh (2014) developed a chaotic biogeography algorithm for size and shape optimization of truss structures. The Levy flight theory developed by French mathematician Paul Levy is based on a random walk theory.…”

Design of Pin Jointed Structures under Stress and Deflection Constraints Using Hybrid Electromagnetism-like Mechanism and Migration Strategy Algorithm

“…Hence, extensive studies have been carried out to develop different optimization methods, ranging from gradient-based search techniques to derivative-free global optimization algorithms. As an alternative to the classical optimization approaches, meta-heuristic optimization techniques such as harmony search (HS) [7] have been widely utilized and improved to solve structural optimization problems characterized by non-convex, dis-continuous, and non-differentiable [8][9][10][11][12][13][14][15][16].…”

“…Hence, extensive studies have been carried out to develop different optimization methods, ranging from gradient-based search techniques to derivative-free global optimization algorithms. As an alternative to the classical optimization approaches, meta-heuristic optimization techniques such as harmony search (HS) algorithm [1], particle swarm optimization (PSO) [2], big bang-big crunch (BB-BC) [3] algorithm, teachinglearning-based optimization (TLBO) [4], Biogeography-Based Optimization (BBO) [5], League Championship Algorithm (LCA) [6], and Cultural Algorithm (CA) [7] have been widely utilized and improved to solve structural optimization problems characterized by non-convex, dis-continuous, and non-differentiable [8][9][10][11][12][13][14][15][16].…”

“…Hence, extensive studies have been carried out to develop different optimization methods, ranging from gradient-based search techniques to derivative-free global optimization algorithms. As an alternative to the classical optimization approaches, meta-heuristic optimization techniques such as harmony search (HS) [7] have been widely utilized and improved to solve structural optimization problems characterized by non-convex, dis-continuous, and non-differentiable [8][9][10][11][12][13][14][15][16].The meta-heuristic algorithms have some advantages such as a simple framework and ease of implementation. Therefore, these algorithms have been adopted by researchers so far and are well suited to solve various structural optimum design problems including the sizing, layout, and topology optimization problems [17][18][19][20][21].…”