Cost optimization of high strength concretes by soft computing techniques

被引:0
作者
Ozbay, Erdogan [1 ]
Oztas, Ahmet [2 ]
Baykasoglu, Adil [3 ]
机构
[1] Mustafa Kemal Univ, Dept Civil Engn, TR-31200 Iskenderun, Turkey
[2] Epoka Univ, Dept Civil Engn, Tirana, Albania
[3] Gaziantep Univ, Dept Ind Engn, TR-27310 Gaziantep, Turkey
关键词
high-strength concrete; genetic algorithm; genetic programming; cost optimization; DESIGN;
D O I
10.12989/cac.2010.7.3.221
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this study 72 different high strength concrete (HSC) mixes were produced according to the Taguchi design of experiment method. The specimens were divided into four groups based on the range of their compressive strengths 40-60, 60-80, 80-100 and 100-125 MPa. Each group included 18 different concrete mixes. The slump and air-content values of each mix were measured at the production time. The compressive strength, splitting tensile strength and water absorption properties were obtained at 28 days. Using this data the Genetic Programming technique was used to construct models to predict mechanical properties of HSC based on its constituients. These models, together with the cost data, were then used with a Genetic Algorithm to obtain an HSC mix that has minimum cost and at the same time meets all the strength and workability requirements. The paper describes details of the experimental results, model development, and optimization results.
引用
收藏
页码:221 / 237
页数:17
相关论文
共 15 条
[1]  
Al-Tabtabai H., 1999, ENG CONSTR ARCHIT MA, V6, P121, DOI [10.1108/eb021105, DOI 10.1108/EB021105]
[2]   Multi-objective optimization in material design and selection [J].
Ashby, MF .
ACTA MATERIALIA, 2000, 48 (01) :359-369
[3]  
Bhatti M.A., 2000, PRACTICAL OPTIMIZATI
[4]  
Bliss D., 2006, Surviving the Pakistan earthquake
[5]   COUPLED USE OF REDUCED INTEGRATION AND NON-CONFORMING MODES IN QUADRATIC MINDLIN PLATE ELEMENT [J].
CHOI, CK ;
KIM, SH .
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 1989, 28 (08) :1909-1928
[6]   An investigation of the use of three selection-based genetic algorithm families when minimizing the production cost of hollow core slabs [J].
de Castilho, VC ;
Nicoletti, MD ;
El Debs, MK .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2005, 194 (45-47) :4651-4667
[7]  
Ferreira C., 2001, Complex Systems, V13, P87
[8]  
Ferreira C., 2002, Gene expression programming in problem solving, in soft computing and Industry: recent applications
[9]  
Goldberg DE., 1989, GENETIC ALGORITHMS S, V13
[10]   Optimization techniques for the design of high-performance fibre-reinforced concrete [J].
Karihaloo, BL ;
Lange-Kornbak, D .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2001, 21 (01) :32-39