CO2 and cost optimization of reinforced concrete footings using a hybrid big bang-big crunch algorithm

TLDR: In this paper, a procedure for the design of reinforced concrete footings subjected to vertical, concentric column loads that satisfies both structural requirements and geotechnical limit states using a hybrid Big Bang-Big Crunch (BB-BC) algorithm is developed.

Abstract: A procedure is developed for the design of reinforced concrete footings subjected to vertical, concentric column loads that satisfies both structural requirements and geotechnical limit states using a hybrid Big Bang-Big Crunch (BB-BC) algorithm. The objectives of the optimization are to minimize cost, CO $_{2}$ emissions, and the weighted aggregate of cost and CO $_{2}$ . Cost is based on the materials and labor required for the construction of reinforced concrete footings and CO $_{2}$ emissions are associated with the extraction and transportation of raw materials; processing, manufacturing, and fabrication of products; and the emissions of equipment involved in the construction process. The cost and CO $_{2}$ objective functions are based on weighted values and are subjected to bending moment, shear force, and reinforcing details specified by the American Concrete Institute (ACI 318-11), as well as soil bearing and displacement limits. Two sets of design examples are presented: low-cost and low-CO $_{2}$ emission designs based solely on geotechnical considerations; and designs that also satisfy the ACI 318-11 code for structural concrete. A multi-objective optimization is applied to cost and CO $_{2}$ emissions. Results are presented that demonstrate the effects of applied load, soil properties, allowable settlement, and concrete strength on designs.