Optimization Design of High-Performance Concrete Based on Genetic Algorithm Toolbox of Matlab

Xie, Xian Song; Yan, Dong; Zheng, Yue Zhai

doi:10.4028/www.scientific.net/amr.250-253.2672

Cited by 6 publications

(3 citation statements)

References 4 publications

(4 reference statements)

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“…Owing to wide use and applicability of GAs, researchers attempted to carry out optimization problems of mix design using GAs and fuzzy techniques. Xie et al (2011) [6] explained the design of high-performance concrete using optimization tool i.e., genetic algorithm toolbox. In this work, authors formulated a mathematical model where the performance of material was considered as constraint and the economic cost as an optimization target.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of concrete mix design using genetic algorithms

Kondapally¹,

Chepuri

Elluri

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Most of the engineering construction projects of bridges, dams consume huge quantities of concrete and other materials. Economical design can be better achieved by optimising the quantities of materials without affecting functionalities of structures. Minimising the proportions or quantities of materials without affecting its functional characteristics in a concrete mix results in most cost efficient design process. This study presents the technique of optimisation of concrete mix design applying Genetic Algorithms using a developed MATLAB program. Concrete mix design was performed for different grades of concrete and water cement ratio. It is observed that the use of Genetic Algorithms resulted in economical mix by minimizing the cement content keeping the strength of concrete unaffected. The study results indicated that quantities of cement have been reduced by about 25-40 kg per cubic meter through mix design using GA technique. This resulted in about 6-10 percent reduction in quantities of cement for various cases of mix design considered in the study. Mix design performed using optimization techniques like GA proved to be efficient when compared to mix design using manual approach. Further, the models for predicting compressive strength under different proportions of materials can also be analyzed using GA approach presented in this study.

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Section: Literature Reviewmentioning

confidence: 99%

Optimization of concrete mix design using genetic algorithms

Kondapally¹,

Chepuri

Elluri

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…The GA could reduce the cost, save the energy, and provide better use value in the engineering practice. [115] overall cost optimization of prestressed concrete (PC) bridges It is concluded that the GA can be effectively used in the overall cost optimization of PC bridges. [116] multi-objective optimization for scheduling a multi-storey building…”

Section: Studied Problem Main Findings and Conclusion Originmentioning

confidence: 99%

Review of Nature-Inspired Optimization Algorithms Applied in Civil Engineering

Obradović

2018

e-GFOS

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Nature has always been an example of perfection and inspiration. In nature, everything has reasons why it is happening exactly the way it does. Nature-inspired optimization algorithms have become a rapidly growing area of research in all areas of life. Ant colonies find the shortest path to food, the evolution of the living world shows adaptation to the world around it. For example, bees find the optimal path to food and back to the hive. Optimization algorithms contribute significantly to solving many complex issues and achieving optimal results. This research paper outlines nature-inspired optimization algorithms, such as ant colonies, artificial immune system s, artificial neural networks, flocks of bats, bee swarms, firefly algorithms, genetic algorithms, and particle swarms. The purpose of this brief overview is to provide an easy-to-understand list of the basic features of the most common nature-inspired optimization algorithms as well as the potential applications of the aforementioned algorithms in civil engineering.

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“…The proposed GA model was successful in reducing the number of trial mixtures with desired properties in the field tests. Xie et al [71] used GA for optimizing the mix proportion design of high performance concrete satisfying the requirements of durability, strength, workability and dimensional stability of concrete. The results were compared with mix proportions in practice to establish the effectiveness of results obtained using GA. Rahman and Jumaat [72] used GA to derive a generalized formulation for determining the optimal quantity of materials used to produce non-slump concrete having minimum possible cost.…”

Section: Concrete MIX Design Applicationsmentioning

confidence: 99%

Applications of Soft Computing in Civil Engineering: A Review

Chandwani¹,

Agrawal²,

Nagar³

2013

IJCA

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The field of engineering is a creative one. The problems encountered in this field are generally unstructured and imprecise influenced by intuitions and past experiences of a designer. The conventional methods of computing relying on analytical or empirical relations become time consuming and labor intensive when posed with real life problems. To study, model and analyze such problems, approximate computer based Soft Computing techniques inspired by the reasoning, intuition, consciousness and wisdom possessed by a human beings are employed. In contrast to conventional computing techniques which rely on exact solutions, soft computing aims at exploiting given tolerance of imprecision, the trivial and uncertain nature of the problem to yield an approximate solution to a problem in quick time. Soft Computing being a multi-disciplinary field uses a variety of statistical, probabilistic and optimization tools which complement each other to produce its three main branches viz., Neural Networks, Genetic Algorithms and Fuzzy Logic. The review paper presents the applications of two major Soft Computing techniques viz., Artificial Neural Networks and Genetic Algorithms in the field of Civil Engineering, which to some extent has replaced the time consuming conventional techniques of computing with intelligent and time saving computing tools.

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Optimization Design of High-Performance Concrete Based on Genetic Algorithm Toolbox of Matlab

Cited by 6 publications

References 4 publications

Optimization of concrete mix design using genetic algorithms

Optimization of concrete mix design using genetic algorithms

Review of Nature-Inspired Optimization Algorithms Applied in Civil Engineering

Applications of Soft Computing in Civil Engineering: A Review

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