Mix proportioning of high-performance concrete by applying the GA and PSO

Subject Areas : International Journal of Smart Electrical Engineering

Alireza rezaee ¹ , mohamad reza hasani ahangar ²

1 - Ph.D. of Electrical Engineering, Islamic Azad university hashtgerd branch, hasthtgerd, Alborz, Iran
2 - Assistant Professor, center of ghadr, Imam hossein university, Tehran, Iran

Received: 2015-04-12 Accepted : 2015-04-12 Published : 2012-03-01

Keywords: High-performance concrete, Genetic Algorithm, particle swarm optimization, Mixture,

Abstract :

High performance concrete is designed to meets special requirements such as high strength, high flowability, and high durability in large scale concrete construction. To obtain such performance many trial mixes are required to find desired combination of materials and there is no conventional way to achieve proper mix proportioning. Genetic algorithm is a global optimization technique based on mechanics of natural selection and natural genetics and can be used to find a near optimal solution to a problem that may have many solutions. Particle swarm optimization is another evolutionary searching strategy motivated by social behaviors to obtain optimum answer. This paper presents a method whereby the mixture proportion of concrete can be optimized to reduce the number of trial mixtures with desired properties by using the genetic algorithm and particle swarm optimization techniques.

References:

[1] A.M. Neville, P.C Aitcin, High-performance concrete- An

overview, 1998.

[2] I. Maruyama, M. Kanematsu, “Optimization of Mix Proportion

of Concrete under Various Severe Conditions by Applying the

Genetic Algorithm”, University of Tokyo, Japan, 2004.

[3] D. Goldberg, Genetic Algorithm in search, optimization and

Machine Learning, Addison Welsley publishing company,

1989.

[4] A. Chipperfield, Genetic algorithm user’s guide for use with

MATLAB, Version 1.2.

[5] J. Singh, PSO MATLAB Toolbox, PSOTOOLBOX Open

Source.2003.

[6] MATLAB, Version 6.5, The Math Works, 2002.