Abstract:
Nowadays, the demand of constructing high-rise (multi-story) buildings is increasing from time to
time in different cities due to land scarcity. The structural design of these reinforced concrete
buildings was performed by Conventional methods of designing, which follows the paradigm
“estimate-analysis-check” made the design process extremely time-consuming, very large design
margins and excessive material usage.
In this research, weight optimization of multi-storied reinforced concrete building under multiple
design criteria was carried out. The research mainly focused on minimizing the weight of
reinforced concrete building while satisfying the limitations and specifications described by EBCS
EN 1992-1-1:2013 design code. Optimization problems were formulated with inclusion of weight
minimization as objective function, design variables and constraint functions. The design variables
were taken as the area of steel and the cross-sectional dimension of the structural members. The
design constraints on dimensions, strength capacities and areas of reinforcement were based on
the specifications of Ethiopia Building Code Standard. As a research study, a four bay, twelve
story RC building was optimized for minimum weight using optimization toolbox in MATLAB
software and Evolutionary algorithm through advanced excel solver as optimizers. The case study
was analyzed under earthquake and gravity loads by coefficient method using commercial
software ETABS. The research has focused on comparing the results of two distinct methods of
optimization and convectional method of design as control. The comparative parameters were
total weight, story displacements and story drifts.
The optimization toolbox in MATLAB and Evolutionary algorithm were able to reduce the
structural weight of this building by 15.89% and 18.801% respectively as compared to the original
design weight. Again, story displacements, and story drift for the optimized building was reduced
by 18.18% and 15.89% for the optimization toolbox in MATLAB and Evolutionary algorithm
respectively as compared to the original design story displacement and drift. In conclusion, as
result showed, optimization tool box in MATLAB reduces total weight than Evolutionary algorithm
embedded in excel solver. So, it is better to use optimization tool box in MATLAB rather than
Evolutionary algorithm embedded in excel solver
