Applications of matlab in optimization of bridge

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Issue: 05 | May-2014, Available @ http://www.ijret.org 34
APPLICATIONS OF MATLAB IN OPTIMIZATION OF BRIDGE
SUPERSTRUCTURES
Rajesh F. Kale1
, N.G.Gore2
, P.J.Salunke3
1
M.E Student, Civil Engineering Dept., M.G.M.’s College of Engineering & Tech. Kamothe, Navi Mumbai
2
Professor, Civil Engineering Dept., M.G.M.’s College of Engineering & Tech. Kamothe, Navi Mumbai
3
Professor, Civil Engineering Dept., M.G.M.’s College of Engineering & Tech. Kamothe, Navi Mumbai
Abstract
Optimization is an act of obtaining the best results under given circumstances. In design, construction and maintenance of any
engineering system engineers have to take many technological and managerial decisions at several stages. The ultimate aim of all
such decisions is either to minimize the efforts required or to maximize the desired benefit. Optimization is a process of finding the
conditions that give the maximum or minimum value of any function. Any engineering system or problem is defined by set of quantities
and these quantities can be classified as design variables, constraints, and objective function. All these quantities collectively form a
optimization problem and this problem can be solved with the help of MATLAB programming language. The optimization problem is
characterized by having a combination of continuous, discrete and integer sets of design variables. MATLAB is a high-level language
and interactive environment for numerical computation, visualization, and programming. Using MATLAB we can analyse data,
develop algorithms, and create models and applications. The language contains tools, and built-in math functions which enable us to
explore multiple approaches and reach a solution faster than with spread sheets or traditional programming languages such as C,
C++, java, Fortran etc. In this present study, cost optimization approach for various bridge superstructures is presented. The main
objective function is to minimize the total cost in the design process of the bridge system considering the cost of materials. The cost of
structural element covers cost of material and labor for reinforcement, concrete and formwork. Design constraints for the
optimization are considered according to Standard Specifications for road bridges. The optimization process is done for different
grades of concrete and steel. The comparative results for different grades of concrete and steel are presented in tabulated form.
Keywords: Bridge superstructure, MATLAB, Structural optimization
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1. INTRODUCTION
Transportation needs commensurate with infrastructural
development which demands shortest routes to cover longer
distances. Such short routes require crossing of number of
obstacles such as rivers, railway lines and existing roads etc.
Bridge structures are the only solutions for such problems.
Bridges are essential and vital elements of any road network.
The lack of bridge or failure of bridge can cause serious
bottlenecks and dislocation of traffic resulting in unacceptably
large economic losses to the country. A bridge may be defined
as a structure providing passage over an obstacle without
closing the way beneath. Various types of bridges are present
today and different types of methods of construction of
bridges are also available such as R.C.C., prestress, steel,
composite bridges etc. The ultimate aim of any engineer is to
select proper type of bridge and proper methodology so as to
construct bridge with economy and with fewer efforts.
In conventional structure design process, the design method
proposes a certain solution that is validated by mathematical
analysis in order to verify that the problem requirements or
specifications are satisfied. If such requirements are not
satisfied, then a new solution is proposed by the designer
based on his intuition experience .The process undergoes
many manual iterations before the design can be finalized
making it a slow and very costly process. There is no formal
attempt to reach the best design in the strict mathematical
sense of minimizing cost. The process of design is relied
exclusively on the designer’s experience, intuition and
creativity resulting in high cost in terms of times and human
efforts. An alternative to the conventional design method is
optimum design. An optimum design normally implies the
most economic structure without harming the functional
purposes of the structure. An optimization technique
transforms the conventional design process of trial and error
into a formal and systematic procedure. Bridge superstructure
generally consists of girder, deck slab, parapet wall, kerbs and
footpaths. In this study cost optimization approach for girder
and deck slab is presented for various bridge superstructures.
The structure is modelled and analyzed using the direct design
method. Optimization problem is formulated is in nonlinear
programming problem (NLPP) by SUMT. The evolution of
bridges from the ancient times to present age is a continues
process and is a result of human desire to use more and more
improved methods and materials in order to build cheaper,

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finer and stronger bridges of any spans and of lasting quality.
The search for further improvement is not over and
experimentations for building cheaper, stronger and
aesthetically better bridges for all times to come.
The method of cost optimization of bridge superstructures can
be applied to any type of bridge superstructures such as I-
girder, T-beam girder and box girder along with deck slab.
The methodology for optimization is similar in all problems of
optimization thus in this paper a single problem of cost
optimization of R.C.C T-beam girder is presented. Referring
to this solution any bridge superstructure can be successfully
optimized.
Macrae et al. (1984) presented a computer approach to the
optimal design of structural concrete beams. An optimal
design program called OSCON was used for this purpose. The
main objective of this study was Minimizing the amount of
reinforcement for a given concrete-section, evaluating the
effect of steel cost ratios on optimal solutions, Optimizing the
section shape of partially pre-stressed concrete beams,
Analysis of given designs with respect to all relevant criteria.
Andres Guerra and Panos D. Kiousis (2006) demonstrated
Design optimization of reinforced concrete structures. A novel
formulation aiming to achieve optimal design of reinforced
concrete (RC) structures is presented. Successful
implementation demonstrates the abilities and performance of
MATLAB’s Sequential quadratic programming algorithm for
the design optimization of RC structures.
2. OPTIMIZATION
Optimization is the act of obtaining the best results under
given circumstances. In design, construction and maintenance
of any engineering system engineers have to take many
technological and managerial decisions at several stages. The
ultimate aim of all such decisions is either to minimize the
effort required or to maximize the desired benefit, since the
effort required or the benefit desired in any practical situation
can be expressed as a function certain decision variables.
Optimization can also be defined as process of finding the
conditions that give the maximum or minimum value of a
function. The ever increasing demand on engineers to lower
production costs to withstand competition has promoted
engineers to look for rigorous methods of decision making,
such as optimization methods, to design and produce products
both economically and efficiency.
3. DESIGN VARIABLES
Any engineering system or component is defined by a set of
quantities some of which are usually fixed at the outset and
these are called as preassigned parameters. Some of which are
variables during design processes and are called as design
variables or decision variables. The various design variables
considered in process of optimization of R.C.C. T-beam girder
are
3.1 ) X1 = Depth of deck slab
3.2 ) X2 = Width of web
3.3 ) X3 = Overall depth of girder
4. DESIGN CONSTRAINTS
In many practical problems design variables cannot be chosen
arbitrarily sometimes they have to satisfy certain specified
functional and other requirements, the restrictions that must be
followed to produce an acceptable design are collectively
called as design constraints. These constraints depend on
physical limitations. If the design meets the entire requirement
placed on it, it is called a feasible design.The various design
constraints considered in process of optimization of R.C.C. T-
beam girder are
Constraint equations are:
4.1) Depth of deck slab constraint G1 = (dsmax/X1)-1< 1
4.2) Shear stress constraint for deck slab G2 = (Tv/Tc)-1< 1
4.3) Steel constraint for deck slab G3 = (AstminSLAB/Ast)-1
<1
4.4) Shear stress constraint for longitudinal girder G4 =
(TvmaxIG/Tvlimit)-1 < 1
4.5) Shear stress constraint for cross girder G5 =
(TvmaxCG/Tvlimit)-1 < 1
4.6) Steel constraint for longitudinal girder G6 =
(AstminGIRDER/AstproLG)-1 < 1
4.7)Steel constraint for cross girder G7 =
(AstminGIRDER/AstproCG)-1 < 1
4.8) Compressive stress constraint for girder G8 =
(O1/Ocbc)-1 < 1
4.9) Tensile stress constraint for girder G9 =
(O2/Ost)-1 < 1
4.10) Overall depth constraint for girder G10 =
(Dmax/X3)-1 < 1
Where, dsmax= minimum depth of slab from bending moment
calculations, Tv = nominal shear stress in slab, Tc =
Permissible shear stress in slab, AstminSLAB = minimum
steel required in slab, Ast = steel provided in slab from
calculations, TvmaxIG = nominal shear stress in longitudinal
girder, deff = effective depth of girder, Tvlimit = limiting
shear stress in girder, TvmaxCG = nominal shear stress in
cross girder, Tvlimit = limiting shear stress in
girderAstminGIRDER = minimum area of steel required in
girder, AstproLG = Area of steel provided in longitudinal
girder from calculations, AstminGIRDER = minimum area of

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steel required in girder, AstproCG = Area of steel provided in
cross girder, O1 = compressive stress in girder, Ocbc =
permissible compressive stress in girder, O2 = Tensile stress
in girder, Ost = permissible Tensile stress in girder, Dmax =
maximum depth of girder.
5. FORMULATION OF OPTIMIZATION
PROBLEM
For a particular girder span and bridge width, a large number
of parameters control the design of the bridge such as girder
spacing, cross sectional dimensions of girder, deck slab
thickness, deck slab reinforcement, concrete strength,
materials of construction, reinforcement in cross girder and
intermediate girders etc. By studying proper design procedures
of R.C.C. T-beam girder we will get preassigned parameters,
design variables or decision variables, design constraints,
design vectors and objective functions. By using these all
parameters we can convert normal design problem of R.C.C.
T-beam girderinto optimization problem and this optimization
problem can be solved with the help of various optimization
techniques or software’s which are available so as to achieve
desired objective function, so as to optimize box girder.
Optimization problem is formulated is in nonlinear
programming problem (NLPP) by SUMT.In SUMT the
constraint minimization problem is converted into
unconstraint one by introducing penalty function. In the
present work is of the form, f(x, r) is the penalty function f(x)
is the objective function r is the non-negative penalty
parameter, and m is the total number of constraints. The
penalty function (x, r) is minimized as an unconstrained
function of x and r, for a fixed value of r. The value of r is
reduced sequent rained and the sequence of minima obtained
converges to the constrained minimum of problems as r 
0.The present optimization problem is solved by the interior
penalty function method. Themethod is used for solving
successive unconstrained minimization problems coupled with
cubic interpolation methods of on dimensional search. The
program developed S. S. RAO for SUMT is used for the
solution of the problem. The program is written in MATLAB
language.The various design variables and constraint
equations used in analysis are explained as earlier.
Fig 1 Cross section of R.C.C. T-beam girder
As shown in above figure X1 = ds, X2 = bw, X3 = D
6. OBJECTIVE FUNCTION
The main objective inthe present optimization problem is to
optimize R.C.C T-beam girder with deck slab system and also
to formulate the problem properly in terms of optimization
problem and so as to solve this optimization problem with the
help of optimization techniques.Objective function to be
satisfied is the cost of R.C.C. T-beam bridge deck whose main
components are cost of concrete and steel. It is assumed that
cost of steel, launching and casting formwork etc. are directly
proportional to volume of concrete, hence all these costs are
included in the rate of concrete.
Objective function can be expressed as:
CONCCOST = QC*RATECONC
STEELCOST = QS*RATESTEEL
TOTAL COST = CONCCOST+STEELCOST
Rate of objective function can be expressed as,
QC= Quantity of concrete in m3
QS= Quantity of steel in Kg
RATECONC= Cost of concrete/ m3
RATESTEEL= Cost of steel/ Kg
7. THE SEQUENTIAL UNCONSTRAINED
MINIMIZATION TECHNIQUE (SUMT)
In SUMT the constraint minimization problem is converted
into unconstraint one by introducing penalty function. In the
present work is of the form, f(x, r) is the penalty function f(x)
is the objective function r is the non-negative penalty
parameter, and m is the total number of constraints. The
penalty function (x, r) is minimized as an unconstrained

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function of x and r, for a fixed value of r. The value of r is
reduced sequent rained and the sequence of minima obtained
converges to the constrained minimum of problems as r  0.
The present optimization problem is solved by the interior
penalty function method. The method is used for solving
successive unconstrained minimization problems coupled with
cubic interpolation methods of on dimensional search. The
program developed by S. S. Rao for SUMT is used for the
solution of the problem. The program is written in Matlab
language.
Methods for the Solution of the NLPP
1. Method of Feasible Directions
2. Sequential Unconstrained Minimization Technique
(SUMT)
3. Sequential Linear Programming (SLP)
4. Dynamic Programming
8. VARIOUS METHODS OF OPTIMIZATION
Mathematical Programming Techniques Stochastic Programming Techniques Statistical Methods
8.1 Mathematical Programming Techniques
1. Calculus Method
2. Calculus Of Variations
3. Nonlinear Programming
4. Geometric Programming
5. Quadratic Programming
6. Linear Programming
7. Dynamic Programming
8. Integer Programming
9. Stochastic Programming
10. Separable Programming
11. Multi Objective Programming
12. Cpm & Pert
13. Game Theory
8.2 Stochastic Programming Techniques
1. Stastical Decision Theory
2. Markov Processes
3. Queuing Theory
4. Renewal Theory
5. Simulation Methods
6. Reliability Theory
8.3 Statistical Method
1. Regression Analysis
2. Cluster Analysis
3. Design of Experiments
4. Discriminate Analysis
9. ILLUSTRATIVE EXAMPLE
For different conditions and start from starting point and end
with optimized point the result shown in graphical form as
below, Typical format of graph
10. SUMMARY
The objective of this study is to investigate an appropriate
optimization method for minimum cost of bridge
superstructures. Parametric study with respect to different
types of spans and grades of concrete and steel for
combinations of girder superstructures has been carried out.
The results of optimum design for girder has been compared
and conclusions drawn. In view of achieving this objective it
is decided to develop a computer code in MATLAB. After
4.50E+05
5.00E+05
5.50E+05
6.00E+05
6.50E+05
1 2 3 4 5 6 7
COSTOFGIRDER
POINTS OF OPTIMIZATION
GRAPHICAL
REPRESENTATION
SP1 - OP1
SP2-OP2
SP3-OP3

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validating this computer code by comparing the results with
analytical results, it is planned to carry out the economical and
safe design.
11. CONCLUSIONS
1. It is possible to formulate and to obtain solution for the
minimum cost design for bridge superstructures with help of
MATLAB and it can be suitable to any type of bridge
superstructure.
2. In present study optimization technique for R.C.C. T-beam
girder is presented and explained, similar technique can be
applied to any bridge superstructure in order to optimize it.
3. It is possible to obtain the global minimum for the
optimization problem by starting from different starting points
with the interior penalty function method.
4. Interior penalty function method can be used for solving
resulting non-linear optimization problems. Exterior penalty
function method can be used for solving resulting non-linear
optimization problems.
5. The minimum cost design of girder is fully constrained
design which is defined as the design bounded by at least as
many constraints as there are the design variables in the
problems.
6. Actual percentage of the saving obtained for optimum
design for girder depend upon the deck slab thickness, depth
of girder, grade of steel and grade of concrete.
7. The cost of bridge superstructures increased rapidly with
respect grade of concrete increases and grade of steel increases
whereas cost decreases as the span of bridge reduces, also the
cost of girder decreases with the increase in the girder depth.
8. Significant savings in cost over the normal design can be
achieved by the optimization. However the actual percentage
of the saving obtained for optimum design for bridge
superstructures depend upon the span of slab and grade of
material.
ACKNOWLEDGEMENTS
I take this opportunity to thank staff members of Civil
Engineering Department, Mahatma Gandhi Mission’s College
of Engineering and Technology, Kamothe, library staff for
their assistance useful views and tips. A word of thanks is also
reserved for all my batch mates for their selfless help, support
and entertaining company.
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