Minimum weight design of reinforced concrete beams utilizing grey wolf and backtracking search optimization algorithms

Abstract

In this study, optimal weight design of a reinforced concrete beam subjected to various loading conditions is investigated. The purpose of the optimization is to attain the minimum weight design of the reinforced concrete beam under distributed and two-point loads. The design problem is handled under three different design load cases. The two-point loads are affected on beam-to-beam connection nodes of reinforced concrete beams. Thus, while the magnitudes of distributed load and two-points load are remained constant, the distances between two-points loads are taken as 2m, 3m and 4m, respectively. The width and height of the rectangular cross-section of the concrete beam, and the diameters of the longitudinal and confinement steel rebars are treated as design variables of the optimum design problem. The design constraints of the optimization problem consist of the geometric constraints and necessities of the Turkish Requirements for Design and Construction of Reinforced Concrete Structures (TS500), and Turkish Building Earthquake Code (TBEC). As two novel metaheuristics, grey wolf (GW) and backtracking search (BS) optimization algorithms are selected as optimizers. Both algorithms are independently operated five times for three different design problems. Thus, the obtained results are examined statistically to compare in accordance with algorithmic performances. The optimal findings from optimization algorithms show that the GW algorithm is a little bit more robust on the exploitation phase, while the BS algorithm is stronger on the exploration phase. Moreover, it can be deducted from optimal beam designs that the GW algorithm is more viable to minimize reinforced concrete beam design.