GENETIC-ALGORITHM-BASED MIX PROPORTION DESIGN METHOD FOR RECYCLED AGGREGATE CONCRETE

Several desirable characteristics of concrete, such as strength, slump, durability and low CO2 emission, cannot always be obtained by current conventional mix proportion design methods lot recycled aggregate concrete (RAC), because Recycled aggregate generally has lower quality than natural aggregate owing to residual cement paste and various impurities." We treat optimal concrete mix proportioning as a multi-criteria problem, and suggest a new method based on genetic algorithms (GAs) to solve the mix proportion design problem for RAC through a simulated biological evolutionary process. In this method, several fitness functions for the desired properties of concrete, i.e., slump, strength, carbonation speed coefficient, price, and emission of CO2, were considered based on conventional data or adopted from previous studies. We thus arrived at optimal mix proportions for RAC that meet the desired performance criteria.