Proceedings of the 12th annual conference on Genetic and evolutionary computation - GECCO '10, 2010
Page 1. Optimum Design of Grillage Systems under Code Provisions using Particle Swarm Optimizatio... more Page 1. Optimum Design of Grillage Systems under Code Provisions using Particle Swarm Optimization Erkan Doğan Res. Assist. Middle East Technical University, Engineering Sciences Department +903122102381 derkan@metu.edu.tr Ferhat Erdal Res. Assist. ...
Cellular beams became increasingly popular as an efficient structural form since their introducti... more Cellular beams became increasingly popular as an efficient structural form since their introduction. Their sophisticated design and profiling process provide greater flexibility in beam proportioning for strength, depth, size and location of circular holes. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Cellular beams are used as primary or secondary floor beams in order to achieve long spans and service integration. In this study, the design problem of cellular beams is formulated as optimum design problem. The minimum weight is taken as the design objective while the design constraints are implemented from The Steel Construction Institute Publication Number 100. The design methods adopted in this publication are consistent with BS5950 parts 1 and 3. The formulation of the design problem considering the limitations of the above mentioned turns out to be a discrete programming problem. Harmony search and particle swarm optimization methods are used for obtaining the solution of the design problem. The design algorithms based on these two techniques select the optimum UB section to be used in the production of a cellular beam subjected to a general loading, the optimum hole diameter and the optimum number of holes in the cellular beam. Furthermore, this selection is also carried out such that the design limitations are satisfied and the weight of the cellular beam is the minimum. A number of design examples are considered to demonstrate the efficiency of the algorithm presented.
Domes are elegant and economical structures
used in covering large areas. They are built in vari... more Domes are elegant and economical structures
used in covering large areas. They are built in various
forms. According to their form, they are given special names
such as lamella, network, and geodesic domes. In this
paper, optimum topological design algorithm is presented
that determines the optimum number of rings, the optimum
height of crown and tubular section designations for
the member groups of these domes. The design algorithm
developed has a routine that generates the data required for
the geometry of these domes automatically. The minimum
weight of each dome is taken as the objective function. The
design constraints are implemented according to the provision
of LRFD-AISC (Load and Resistance Factor Design–
American Institute of Steel Constitution). The optimum
topological design problem that considers these constraints
turns out to be discrete programming problem. Improved
harmony search algorithm is suggested to determine its
optimum solution. The design algorithm also considers the
geometric nonlinearity of these dome structures. Design
examples are presented to demonstrate the effectiveness and
robustness of the design optimization algorithm developed.
ABSTRACT The objective of the current research is to present ultimate load carrying capacities an... more ABSTRACT The objective of the current research is to present ultimate load carrying capacities and finite element analysis of optimally designed steel cellular beams under loading conditions. The tests have been carried out on twelve full-scale non-composite cellular beams. There are three different types of NPI_CB_240, NPI_CB_260 and NPI_CB_280 I-section beams, and four tests have been conducted for each specimen. These optimally designed beams which have beginning span lengths of 3000 mm are subjected to point load acting in the middle of upper flange. The design method for the beams is the harmony search method and the design constraints are implemented from BS 5950 provisions. The last part of the study focuses on performing a numerical study on steel cellular beams by utilizing finite element analysis. The finite element method has been used to simulate the experimental work by using finite element modeling to verify the test results and to investigate the nonlinear behavior of failure modes such as web-post buckling and Vierendeel bending of steel cellular beams.
This study aims at improving the performance
of simulated annealing (SA) search technique in rea... more This study aims at improving the performance
of simulated annealing (SA) search technique in real-size
structural optimization applications with practical design
considerations. It is noted that a standard SA algorithm
usually fails to produce acceptable solutions to such problems
associated with its poor convergence characteristics
and incongruity with theoretical considerations. In the paper
novel approaches are developed and incorporated into the
standard SA algorithm to eliminate the observed drawbacks
of the technique. The performance of the resulting
(improved) algorithm is investigated in conjunction with
two numerical examples (a 304-member braced planar
steel frame, and 132-member unbraced space steel frame)
designed according to provisions of the Allowable Stress
Design (ASD) specification. In both examples, curves showing
the variation of average acceptance probability parameter
in standard and improved algorithms are plotted to verify
usefulness and robustness of the integrated approaches.
There is a noticeable increase in the emergence of non-deterministic search techniques that simul... more There is a noticeable increase in the emergence of non-deterministic search techniques that simulate natural phenomena into a numerical optimization technique in recent years. These techniques are used for developing structural optimization algorithms that are particularly effective for obtaining solutions to discrete programming problems. In this study amongst these techniques genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search are utilized to develop seven optimum design algorithms for real size rigidly connected steel frames. The design problems are formulated according to ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution).
In recent years a number of metaheuristic search techniques have been widely used in developing s... more In recent years a number of metaheuristic search techniques have been widely used in developing structural optimization algorithms. Amongst these techniques are genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search. The primary goal of this paper is to objectively evaluate the performance of abovementioned seven techniques in optimum design of pin jointed structures. First, a verification of the algorithms used to implement the techniques is carried out using a benchmark problem from the literature. Next, the techniques compiled in an unbiased coding platform are evaluated and compared in terms of their solution accuracies as well as convergence rates and reliabilities using four real size design examples formulated according to the design limitations imposed by ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution). The results reveal that simulated annealing and evolution strategies are the most powerful techniques, and harmony search and simple genetic algorithm methods can be characterized by slow convergence rates and unreliable search performance in large-scale problems.
Many optimization techniques have been proposed since the inception of engineering
optimization ... more Many optimization techniques have been proposed since the inception of engineering
optimization in 1960s. Traditional mathematical modeling-based approaches are
incompetent to solve the engineering optimization problems, as these problems have
complex system that involves large number of design variables as well as equality or
inequality constraints. In order to overcome the various difficulties encountered in
obtaining the solution of these problems, new techniques called metaheuristic algorithms
are suggested. These techniques are numerical optimization algorithms that are based on a
natural phenomenon. In this study, a state-of-art improved harmony search method with a
new adaptive error strategy is proposed to handle the design constraints. Number of
numerical examples is presented to demonstrate the efficiency of the proposed algorithm
in solving engineering optimization problems.
Sustainable construction aims at reducing the environmental impact of buildings on human health a... more Sustainable construction aims at reducing the environmental impact of buildings on human health and natural environment by efficiently using energy, resources and reducing waste and pollution. Building construction has the capacity to make a major contribution to a more sustainable future of our World because this industry is one of the largest contributors to global warming. The use of cold-formed steel framing in construction industry provides sustainable construction which requires less material to carry the same load compare to other materials and reduces amount of waste material at a site. In this study five optimum design algorithms are developed for cold-formed steel frames made of thin-walled sections using the recent metaheuristic techniques. The algorithms considered are firefly, cuckoo search, artificial bee colony with levy flight, biogeography-based optimization and teaching-learning-based optimization algorithms. The design algorithms select the cold-formed thin-walled C-sections listed in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design) in such a way that the design constraints specified by the code are satisfied and the weight of the steel frame is the minimum. A real size cold-formed steel building is optimized by using each of these algorithms and their performance in attaining the optimum designs is compared.
Sustainable development in construction industry is emerging as a major issue among cities and co... more Sustainable development in construction industry is emerging as a major issue among cities and communities in the current century. As global climate change becomes an increasingly serious concern for the future and construction industry dependence on fossil fuels for energy creates greater adverse influence on human health and natural environment, an interest in high-efficient, low environmental impact buildings has begun to transform the notion of building design, construction, and operation. As it stands, the most of the standard buildings in the world consume an extraordinary amount of resources while taking an enormous toll on the environment. The utilization of cold-formed thin-walled open steel sections in structural sites supplies green structural opportunities demanding less material and cost while providing high strength. The developed algorithm for this study obtains the optimum geometric dimensions of cold-formed thin-walled open steel sections under various external loading. Moreover, this design algorithm takes into account of the effect of geometric nonlinearity as well as effect of warping. Also the displacement and stress constraints are included in the formulation of the design problem. The optimum design problem obtained turn out to be mixed integer and discrete programming problem. Artificial Bee Colony (ABC) algorithm is used to obtain its solution. This technique is a recent numerical optimization technique which mimics the intelligent behavior of honey bee swarm. The recent studies with the ABC method have shown its effectiveness and robustness in finding the optimum solution of combinatorial optimization problems. A design example is included to demonstrate the efficiency of the optimum design algorithm developed.
Proceedings of the 12th annual conference on Genetic and evolutionary computation - GECCO '10, 2010
Page 1. Optimum Design of Grillage Systems under Code Provisions using Particle Swarm Optimizatio... more Page 1. Optimum Design of Grillage Systems under Code Provisions using Particle Swarm Optimization Erkan Doğan Res. Assist. Middle East Technical University, Engineering Sciences Department +903122102381 derkan@metu.edu.tr Ferhat Erdal Res. Assist. ...
Cellular beams became increasingly popular as an efficient structural form since their introducti... more Cellular beams became increasingly popular as an efficient structural form since their introduction. Their sophisticated design and profiling process provide greater flexibility in beam proportioning for strength, depth, size and location of circular holes. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Cellular beams are used as primary or secondary floor beams in order to achieve long spans and service integration. In this study, the design problem of cellular beams is formulated as optimum design problem. The minimum weight is taken as the design objective while the design constraints are implemented from The Steel Construction Institute Publication Number 100. The design methods adopted in this publication are consistent with BS5950 parts 1 and 3. The formulation of the design problem considering the limitations of the above mentioned turns out to be a discrete programming problem. Harmony search and particle swarm optimization methods are used for obtaining the solution of the design problem. The design algorithms based on these two techniques select the optimum UB section to be used in the production of a cellular beam subjected to a general loading, the optimum hole diameter and the optimum number of holes in the cellular beam. Furthermore, this selection is also carried out such that the design limitations are satisfied and the weight of the cellular beam is the minimum. A number of design examples are considered to demonstrate the efficiency of the algorithm presented.
Domes are elegant and economical structures
used in covering large areas. They are built in vari... more Domes are elegant and economical structures
used in covering large areas. They are built in various
forms. According to their form, they are given special names
such as lamella, network, and geodesic domes. In this
paper, optimum topological design algorithm is presented
that determines the optimum number of rings, the optimum
height of crown and tubular section designations for
the member groups of these domes. The design algorithm
developed has a routine that generates the data required for
the geometry of these domes automatically. The minimum
weight of each dome is taken as the objective function. The
design constraints are implemented according to the provision
of LRFD-AISC (Load and Resistance Factor Design–
American Institute of Steel Constitution). The optimum
topological design problem that considers these constraints
turns out to be discrete programming problem. Improved
harmony search algorithm is suggested to determine its
optimum solution. The design algorithm also considers the
geometric nonlinearity of these dome structures. Design
examples are presented to demonstrate the effectiveness and
robustness of the design optimization algorithm developed.
ABSTRACT The objective of the current research is to present ultimate load carrying capacities an... more ABSTRACT The objective of the current research is to present ultimate load carrying capacities and finite element analysis of optimally designed steel cellular beams under loading conditions. The tests have been carried out on twelve full-scale non-composite cellular beams. There are three different types of NPI_CB_240, NPI_CB_260 and NPI_CB_280 I-section beams, and four tests have been conducted for each specimen. These optimally designed beams which have beginning span lengths of 3000 mm are subjected to point load acting in the middle of upper flange. The design method for the beams is the harmony search method and the design constraints are implemented from BS 5950 provisions. The last part of the study focuses on performing a numerical study on steel cellular beams by utilizing finite element analysis. The finite element method has been used to simulate the experimental work by using finite element modeling to verify the test results and to investigate the nonlinear behavior of failure modes such as web-post buckling and Vierendeel bending of steel cellular beams.
This study aims at improving the performance
of simulated annealing (SA) search technique in rea... more This study aims at improving the performance
of simulated annealing (SA) search technique in real-size
structural optimization applications with practical design
considerations. It is noted that a standard SA algorithm
usually fails to produce acceptable solutions to such problems
associated with its poor convergence characteristics
and incongruity with theoretical considerations. In the paper
novel approaches are developed and incorporated into the
standard SA algorithm to eliminate the observed drawbacks
of the technique. The performance of the resulting
(improved) algorithm is investigated in conjunction with
two numerical examples (a 304-member braced planar
steel frame, and 132-member unbraced space steel frame)
designed according to provisions of the Allowable Stress
Design (ASD) specification. In both examples, curves showing
the variation of average acceptance probability parameter
in standard and improved algorithms are plotted to verify
usefulness and robustness of the integrated approaches.
There is a noticeable increase in the emergence of non-deterministic search techniques that simul... more There is a noticeable increase in the emergence of non-deterministic search techniques that simulate natural phenomena into a numerical optimization technique in recent years. These techniques are used for developing structural optimization algorithms that are particularly effective for obtaining solutions to discrete programming problems. In this study amongst these techniques genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search are utilized to develop seven optimum design algorithms for real size rigidly connected steel frames. The design problems are formulated according to ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution).
In recent years a number of metaheuristic search techniques have been widely used in developing s... more In recent years a number of metaheuristic search techniques have been widely used in developing structural optimization algorithms. Amongst these techniques are genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search. The primary goal of this paper is to objectively evaluate the performance of abovementioned seven techniques in optimum design of pin jointed structures. First, a verification of the algorithms used to implement the techniques is carried out using a benchmark problem from the literature. Next, the techniques compiled in an unbiased coding platform are evaluated and compared in terms of their solution accuracies as well as convergence rates and reliabilities using four real size design examples formulated according to the design limitations imposed by ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution). The results reveal that simulated annealing and evolution strategies are the most powerful techniques, and harmony search and simple genetic algorithm methods can be characterized by slow convergence rates and unreliable search performance in large-scale problems.
Many optimization techniques have been proposed since the inception of engineering
optimization ... more Many optimization techniques have been proposed since the inception of engineering
optimization in 1960s. Traditional mathematical modeling-based approaches are
incompetent to solve the engineering optimization problems, as these problems have
complex system that involves large number of design variables as well as equality or
inequality constraints. In order to overcome the various difficulties encountered in
obtaining the solution of these problems, new techniques called metaheuristic algorithms
are suggested. These techniques are numerical optimization algorithms that are based on a
natural phenomenon. In this study, a state-of-art improved harmony search method with a
new adaptive error strategy is proposed to handle the design constraints. Number of
numerical examples is presented to demonstrate the efficiency of the proposed algorithm
in solving engineering optimization problems.
Sustainable construction aims at reducing the environmental impact of buildings on human health a... more Sustainable construction aims at reducing the environmental impact of buildings on human health and natural environment by efficiently using energy, resources and reducing waste and pollution. Building construction has the capacity to make a major contribution to a more sustainable future of our World because this industry is one of the largest contributors to global warming. The use of cold-formed steel framing in construction industry provides sustainable construction which requires less material to carry the same load compare to other materials and reduces amount of waste material at a site. In this study five optimum design algorithms are developed for cold-formed steel frames made of thin-walled sections using the recent metaheuristic techniques. The algorithms considered are firefly, cuckoo search, artificial bee colony with levy flight, biogeography-based optimization and teaching-learning-based optimization algorithms. The design algorithms select the cold-formed thin-walled C-sections listed in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design) in such a way that the design constraints specified by the code are satisfied and the weight of the steel frame is the minimum. A real size cold-formed steel building is optimized by using each of these algorithms and their performance in attaining the optimum designs is compared.
Sustainable development in construction industry is emerging as a major issue among cities and co... more Sustainable development in construction industry is emerging as a major issue among cities and communities in the current century. As global climate change becomes an increasingly serious concern for the future and construction industry dependence on fossil fuels for energy creates greater adverse influence on human health and natural environment, an interest in high-efficient, low environmental impact buildings has begun to transform the notion of building design, construction, and operation. As it stands, the most of the standard buildings in the world consume an extraordinary amount of resources while taking an enormous toll on the environment. The utilization of cold-formed thin-walled open steel sections in structural sites supplies green structural opportunities demanding less material and cost while providing high strength. The developed algorithm for this study obtains the optimum geometric dimensions of cold-formed thin-walled open steel sections under various external loading. Moreover, this design algorithm takes into account of the effect of geometric nonlinearity as well as effect of warping. Also the displacement and stress constraints are included in the formulation of the design problem. The optimum design problem obtained turn out to be mixed integer and discrete programming problem. Artificial Bee Colony (ABC) algorithm is used to obtain its solution. This technique is a recent numerical optimization technique which mimics the intelligent behavior of honey bee swarm. The recent studies with the ABC method have shown its effectiveness and robustness in finding the optimum solution of combinatorial optimization problems. A design example is included to demonstrate the efficiency of the optimum design algorithm developed.
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used in covering large areas. They are built in various
forms. According to their form, they are given special names
such as lamella, network, and geodesic domes. In this
paper, optimum topological design algorithm is presented
that determines the optimum number of rings, the optimum
height of crown and tubular section designations for
the member groups of these domes. The design algorithm
developed has a routine that generates the data required for
the geometry of these domes automatically. The minimum
weight of each dome is taken as the objective function. The
design constraints are implemented according to the provision
of LRFD-AISC (Load and Resistance Factor Design–
American Institute of Steel Constitution). The optimum
topological design problem that considers these constraints
turns out to be discrete programming problem. Improved
harmony search algorithm is suggested to determine its
optimum solution. The design algorithm also considers the
geometric nonlinearity of these dome structures. Design
examples are presented to demonstrate the effectiveness and
robustness of the design optimization algorithm developed.
of simulated annealing (SA) search technique in real-size
structural optimization applications with practical design
considerations. It is noted that a standard SA algorithm
usually fails to produce acceptable solutions to such problems
associated with its poor convergence characteristics
and incongruity with theoretical considerations. In the paper
novel approaches are developed and incorporated into the
standard SA algorithm to eliminate the observed drawbacks
of the technique. The performance of the resulting
(improved) algorithm is investigated in conjunction with
two numerical examples (a 304-member braced planar
steel frame, and 132-member unbraced space steel frame)
designed according to provisions of the Allowable Stress
Design (ASD) specification. In both examples, curves showing
the variation of average acceptance probability parameter
in standard and improved algorithms are plotted to verify
usefulness and robustness of the integrated approaches.
phenomena into a numerical optimization technique in recent years. These techniques are used for
developing structural optimization algorithms that are particularly effective for obtaining solutions to
discrete programming problems. In this study amongst these techniques genetic algorithms, simulated
annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony
search are utilized to develop seven optimum design algorithms for real size rigidly connected steel
frames. The design problems are formulated according to ASD-AISC (Allowable Stress Design Code of
American Institute of Steel Institution).
optimization algorithms. Amongst these techniques are genetic algorithms, simulated annealing,
evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search.
The primary goal of this paper is to objectively evaluate the performance of abovementioned seven techniques
in optimum design of pin jointed structures. First, a verification of the algorithms used to implement
the techniques is carried out using a benchmark problem from the literature. Next, the techniques
compiled in an unbiased coding platform are evaluated and compared in terms of their solution accuracies
as well as convergence rates and reliabilities using four real size design examples formulated according
to the design limitations imposed by ASD-AISC (Allowable Stress Design Code of American Institute of
Steel Institution). The results reveal that simulated annealing and evolution strategies are the most powerful
techniques, and harmony search and simple genetic algorithm methods can be characterized by
slow convergence rates and unreliable search performance in large-scale problems.
optimization in 1960s. Traditional mathematical modeling-based approaches are
incompetent to solve the engineering optimization problems, as these problems have
complex system that involves large number of design variables as well as equality or
inequality constraints. In order to overcome the various difficulties encountered in
obtaining the solution of these problems, new techniques called metaheuristic algorithms
are suggested. These techniques are numerical optimization algorithms that are based on a
natural phenomenon. In this study, a state-of-art improved harmony search method with a
new adaptive error strategy is proposed to handle the design constraints. Number of
numerical examples is presented to demonstrate the efficiency of the proposed algorithm
in solving engineering optimization problems.
used in covering large areas. They are built in various
forms. According to their form, they are given special names
such as lamella, network, and geodesic domes. In this
paper, optimum topological design algorithm is presented
that determines the optimum number of rings, the optimum
height of crown and tubular section designations for
the member groups of these domes. The design algorithm
developed has a routine that generates the data required for
the geometry of these domes automatically. The minimum
weight of each dome is taken as the objective function. The
design constraints are implemented according to the provision
of LRFD-AISC (Load and Resistance Factor Design–
American Institute of Steel Constitution). The optimum
topological design problem that considers these constraints
turns out to be discrete programming problem. Improved
harmony search algorithm is suggested to determine its
optimum solution. The design algorithm also considers the
geometric nonlinearity of these dome structures. Design
examples are presented to demonstrate the effectiveness and
robustness of the design optimization algorithm developed.
of simulated annealing (SA) search technique in real-size
structural optimization applications with practical design
considerations. It is noted that a standard SA algorithm
usually fails to produce acceptable solutions to such problems
associated with its poor convergence characteristics
and incongruity with theoretical considerations. In the paper
novel approaches are developed and incorporated into the
standard SA algorithm to eliminate the observed drawbacks
of the technique. The performance of the resulting
(improved) algorithm is investigated in conjunction with
two numerical examples (a 304-member braced planar
steel frame, and 132-member unbraced space steel frame)
designed according to provisions of the Allowable Stress
Design (ASD) specification. In both examples, curves showing
the variation of average acceptance probability parameter
in standard and improved algorithms are plotted to verify
usefulness and robustness of the integrated approaches.
phenomena into a numerical optimization technique in recent years. These techniques are used for
developing structural optimization algorithms that are particularly effective for obtaining solutions to
discrete programming problems. In this study amongst these techniques genetic algorithms, simulated
annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony
search are utilized to develop seven optimum design algorithms for real size rigidly connected steel
frames. The design problems are formulated according to ASD-AISC (Allowable Stress Design Code of
American Institute of Steel Institution).
optimization algorithms. Amongst these techniques are genetic algorithms, simulated annealing,
evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search.
The primary goal of this paper is to objectively evaluate the performance of abovementioned seven techniques
in optimum design of pin jointed structures. First, a verification of the algorithms used to implement
the techniques is carried out using a benchmark problem from the literature. Next, the techniques
compiled in an unbiased coding platform are evaluated and compared in terms of their solution accuracies
as well as convergence rates and reliabilities using four real size design examples formulated according
to the design limitations imposed by ASD-AISC (Allowable Stress Design Code of American Institute of
Steel Institution). The results reveal that simulated annealing and evolution strategies are the most powerful
techniques, and harmony search and simple genetic algorithm methods can be characterized by
slow convergence rates and unreliable search performance in large-scale problems.
optimization in 1960s. Traditional mathematical modeling-based approaches are
incompetent to solve the engineering optimization problems, as these problems have
complex system that involves large number of design variables as well as equality or
inequality constraints. In order to overcome the various difficulties encountered in
obtaining the solution of these problems, new techniques called metaheuristic algorithms
are suggested. These techniques are numerical optimization algorithms that are based on a
natural phenomenon. In this study, a state-of-art improved harmony search method with a
new adaptive error strategy is proposed to handle the design constraints. Number of
numerical examples is presented to demonstrate the efficiency of the proposed algorithm
in solving engineering optimization problems.