CO2 and cost optimization of reinforced concrete frames using a big bang-big crunch algorithm
Abstract
A hybrid Big Bang-Big Crunch (BB-BC) optimization algorithm is applied to the design of reinforced concrete frames. The objective of the optimization is to minimize the total cost or the CO2 emissions associated with construction of reinforced concrete frames subjected to constraints based on the specifications and guidelines prescribed by the American Concrete Institute (ACI 318-08).Designs are presented for several reinforced concrete frames that minimize the cost and the CO2 emissions associated with construction. In the first frame example, low-cost designs developed using BB-BC optimization are compared to designs developed using a genetic algorithm. In the second set of frame designs, both low-cost designs using BB-BC optimization are compared to designs developed using simulated annealing. The BB-BC algorithm generated designs that reduced the cost and the CO2 emissions of construction for example frames. © 2012 Elsevier Ltd.
Publication Title
Engineering Structures
Recommended Citation
Camp, C., & Huq, F. (2013). CO2 and cost optimization of reinforced concrete frames using a big bang-big crunch algorithm. Engineering Structures, 48, 363-372. https://doi.org/10.1016/j.engstruct.2012.09.004
