Open AccessParameter tuning in the process of optimization of reinforced concrete structures
Author(s) -
Iván Negrin,
Ernesto L. Chagoyén,
Alejandro Negrin-Montecelo
Publication year - 2021
Publication title -
dyna
Language(s) - English
Resource type - Journals
eISSN - 2346-2183
pISSN - 0012-7353
DOI - 10.15446/dyna.v88n216.87169
Subject(s) - benchmark (surveying) , heuristics , process (computing) , mathematical optimization , superstructure , frame (networking) , reinforced concrete , function (biology) , reinforcement , computer science , optimization problem , structural engineering , mathematics , engineering , geology , telecommunications , geodesy , evolutionary biology , biology , operating system
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.