<p>This paper discusses the application of Genetic Algorithms (GA) in the design optimization of concrete frames that are resistant against seismic loads. The application of GA to the optimization of concrete frames is discussed. After this, the Concrete Optimization Program (COP) and its 4 main components are discussed briefly. The performance of the COP using different GA constants and improved operators were tested on a 2-storey frame. From the initial results, it can be observed that using simple GA with enhancements is insufficient to provide a practical and efficient means of optimizing a concrete frame. In light of this situation, the modified leader reproduction (MLR) was conceived to improve the overall performance of the COP. The performance of the COP with MLR was tested on both a 2-storey and 4-storey frame. From the results, it was confirmed that using MLR enhanced the efficiency and capability of the COP to yield economical and feasible results.</p>
<p>High-strength concrete (HSC) is a highly complex and evolving construction material. Careful selection of constituent materials must be employed to successfully proportion HSC mixtures. While there are codes like ACI and ASTM which guide concrete proportioning, batching companies perform trial and error to produce a number of trial mixes depending on a required strength and slump. This method, however, is costly, time consuming and sometimes uneconomical and wasteful. Hence, genetic algorithms (GA) was explored in deriving optimum HSC mix designs using data collected from a batching company. Verification was implemented through in-situ adjustments and compression tests resulted to be applicable in actual practice that suggested a reduction in the number of trial mixtures and lesser incurred overall material cost of HSC.</p>
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