• Structural Engineering and Mechanics
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• v.45 no.5
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• pp.643-654
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• 2013

Optimum cost design of columns subjected to axial force and uniaxial bending moment is presented in this paper. In the formulation of the optimum design problem, the height and width of the column, diameter and number of reinforcement bars are treated as design variables. The design constraints are implemented according to ACI 318-08 and studies in the literature. The objective function is taken as the cost of unit length of the column consisting the cost of concrete, steel, and shuttering. The solution of the design problem is obtained using the artificial bee colony algorithm which is one of the recent additions to metaheuristic techniques. The Artificial Bee Colony Algorithm is imitated the foraging behaviors of bee swarms. In application of this algorithm to the constraint problem, Deb's constraint handling method is used. Obtained results showed that the optimum value of numerical example is nearly same with the existing values in the literature.

• Steel and Composite Structures
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• v.7 no.6
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• pp.421-440
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• 2007

An optimal design method in cooperated with nonlinear inelastic analysis is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are load-carrying capacity, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.660-664
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• 2003

The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.95-100
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• 1990

An optimization method has been developed to find the minimum weight design of steel building structures which consist of the commercially available discrete sections. In this study, an emphasis was particularly placed on the practical applicability of optimization algorithm in engineering practice. The structure Is optimized through element optimization under the element level constraints first and then, if there is any violation of structural level constraints, it is adequately compensated by the constraint error correction vector obtained through the sensitivity analysis. A scaling procedure is introduced for the problems of large violated displacement constraint. The oscillation control in the objective function is also discussed. By dividing the available H-sections into two groups based on their section characteristics, much improved relationships between section variables were obtained and used efficiently in searching the optimum section in the section table.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.139-148
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• 2009

In a real-life supply chain environment, demand forecasting is usually represented by probabilistic distributions due to the uncertainty inherent in customer demands. However, the customer demand used for an actual supply chain planning is a single deterministic value for each of periods. In this paper we study the choice of single demand value among of the given customer demand distribution for a period to be used in the supply chain planning. This paper considers distributed multi-echelon supply chain and the objective function of this paper is to minimize the total costs, that is the sum of holding and backorder costs over the distribution network under the service level constraint, by using demand selection scheme. Some useful findings are derived from various simulation-based experiments.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.145-152
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• 2003

An optimal design method in cooperated with nonlinear inelastic analysis method is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm uses a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used among sections in the database to look for high performance ones. They satisfy the constraint functions and give the lightest weight to the structure. The objective function is set to the total weight of the steel structure and the constraint functions are load-carrying capacities, serviceability, and ductility requirement. Case studies of a three-dimensional frame and a three-dimensional steel arch bridge are presented.

• Structural Engineering and Mechanics
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• v.17 no.5
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• pp.707-725
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• 2004

An optimal design method with nonlinear elastic analysis is presented. The proposed nonlinear elastic method overcomes the drawback of the conventional LRFD method that accounts for nonlinear effect by using the moment amplification factors of $B_1$ and $B_2$. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are employed to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are strength, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• Korean Journal of Chemical Engineering
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• v.36 no.3
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• pp.356-367
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• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• Computers and Concrete
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• v.10 no.3
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• pp.295-306
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• 2012

Optimum cost design of a simply supported reinforced concrete beam is presented in this paper. In the formulation of the optimum design problem, the height and width of the beam, and reinforcement steel area are treated as design variables. The design constraints are implemented according to ACI 318-08 and studies in the literature. The objective function is taken as the cost of unit length of the beam consisting the cost of concrete, steel and shuttering. The solution of the design problem is obtained using the artificial bee colony algorithm which is one of the recent additions to metaheuristic techniques. The artificial bee colony algorithm is imitated the foraging behaviors of bee swarms. In application of this algorithm to the constraint problem, Deb's constraint handling method is used. Obtained results showed that the optimum value of numerical example is nearly same with the existing values in the literature.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.83-99
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• 2002

Optimality conditions are derived for a nonlinear program in which a support function appears in the objective as well as in each constraint function. Wolfe and Mond-Weir type duals to this program are presented and various duality results are established under suitable convexity and generalized convexity assumptions. Special cases that often occur in the literature are those in which a support function is the square root of a positive semi- definite quadratic form or an Lp norm. It is pointed out that these special cases can easily be generated from our results.