A study of computational design optimization of concrete mixes

This paper presents a thorough overview of optimization research on the design and proportioning of concrete mixes. The necessity for designers and decision-makers to proportion concrete mixes that meet various sometimes conflicting performance criteria, including as cost, workability, mechanical characteristics, durability, and environmental sustainability, is driving mixture design optimization. We begin with a discussion of typical mathematical problem formulations, choices, goals, and constraints related to concrete mixture design optimization in this study. Following that, we look at the many kinds of models used to simulate concrete characteristics, such as a range of linear combination, statistical, machine learning, and physics-based models that are needed to optimize a mixture's proportions. Then, in the context of the material reviewed, we examine and discuss computer techniques for optimizing concrete mixes. Finally, in light of the present state of the art, we highlight and analyze current trends and possibilities for improving the area of concrete mixture design optimization.