Parameter tuning in the process of optimization of reinforced concrete structures

Abstract

Parameter tuning deals with finding the best parameter configuration of an optimization method in a given problem. In structural optimization, it could be an extensive and high-computing cost process. One way to avoid this drawback is to use analytical functions (or benchmark functions), for simulating main features of objective functions in real problems. In this paper, Biogeography-Based Optimization is applied during structural optimization of reinforced concrete frame structures, and Ackley function for parameter tuning in real cases simulation. The tuned method outperformed other meta-heuristics in the actual optimization problem. Structural results show that by not including static soil-structure interaction, differences in direct cost of the superstructure of up to 4.42% are obtained for predominantly cohesive soils and 11.55% for predominantly frictional ones. In beams, L/h ratios around 15 and high reinforcement ratios are highly recommended. In columns and shallow foundations, best rectangularity reaches values of 1.15 and 2.00 respectively.

Optimal Design of Reinforced Concrete Frame Structures Using Cascade Optimization Method

“…For investigation, the relationship between optimal cost and optimal CO2 emissions the considered procedure is applied to RC frames. In Negrin-Diaz et al [26] research, Biogeography-Based Optimization is used for optimization of reinforced concrete structures. Shakedown method is used for evaluate plastic limit load and plastic design parameters in pile foundations to which horizontal loads are applied in the research of Rad and Ibrahim [27].…”