A Hybrid of Firefly and Biogeography-Based Optimization Algorithms for Optimal Design of Steel Frames
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RESEARCH ARTICLE-CIVIL ENGINEERING
A Hybrid of Firefly and Biogeography-Based Optimization Algorithms for Optimal Design of Steel Frames Hamid Farrokh Ghatte1 Received: 1 July 2020 / Accepted: 5 November 2020 © King Fahd University of Petroleum & Minerals 2020
Abstract The principle purpose of the current study is to hybridize firefly algorithm (FA) as a nature-inspired meta-heuristic developed based on the flashing patterns and biogeography-based optimization (BBO) to present a qualified algorithm in the case of optimization of steel frame (SF) structures. In the proposed meta-heuristic algorithm, FA works as a global search engine while BBO achieves the local search task. The proposed algorithm is termed as a firefly algorithm–biogeography-based optimization (FA–BBO). FA–BBO algorithm was employed for the optimization of benchmark SF problems for the validity in the case of a new algorithm. The numerical outputs demonstrate that the new FA–BBO algorithm presents a better computational performance in the comparison of the current algorithms. Keywords Biogeography-based optimization · Firefly algorithm · Meta-heuristic · Optimization steel structures
1 Introduction Design of the structures with minimum weight or minimize an objective function value based on the minimal cost of the structures, regarding the design criteria, is the main purpose for structural optimization [1–5]. Mathematical programming methods have widely been applied in solid and structural optimization [6–9]. During the past few decades, several optimization algorithms have been improved for different structural systems like truss and steel frame (SF) structures [10–18]. As well as, the performance-based design of SFs utilizing meta-heuristic optimization algorithms has been developed by the researchers [19–21]. The metaheuristic algorithms have remarkable characteristics that vary from the gradient-based methods. This class of optimization methods not only demands no gradient computations but also they are straightforward for computer programming. Employing meta-heuristic algorithms allows exploration of a further fraction of the design space in comparison with gradient-based optimization methods. The meta-heuristics illustrate the effectiveness of numerous optimized structural issues like SFs or truss [22–26]. Many researchers employed
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Hamid Farrokh Ghatte [email protected]; [email protected] Civil Engineering Department, Faculty of Engineering, Antalya Bilim University, Antalya, Turkey
popular meta-heuristics such as genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO) and harmony search (HS) for the optimization of structural systems. In the present study, the firefly algorithm (FA) [27], biogeography-based optimization (BBO) [28] and their combination are focused. FA is a recently developed nature-inspired meta-heuristic based on the flashing patterns and behavior of fireflies. Additionally, FA is more efficient in comparison with other design optimization strategies since requires a lo
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