• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.541-548
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• 2006

This study presents a structural cost optimization method for building frame system using high-strength steel members. In, this optimization method, the material cost of steel member is involved in objective function to find the optimal cost of building frame systems. Genetic Algorithm is adopted to optimizer to find structural cost optimization. The proposed adapted to structural design of 3.5 stories example buildings with buildings frame systems. As a result, The proposed optimization method can be effectively adapted to cost optimization of building frame systems using high-strength steel members.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.790-797
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• 2007

This paper proposes a new measure of cost function ruggedness in local optimization with DEAS. DEAS is a computational optimization method developed since 2002 and has been applied to various engineering fields with success. Since DEAS is a recent optimization method which is rarely introduced in Korean, this paper first provides a brief overview and description of DEAS. In minimizing cost function with this non-gradient method, information on function shape measured automatically will enhance search capability. Considering the search strategies of DEAS are well designed with binary matrix structures, analysis of search behaviors will produce beneficial shape information. This paper deals with a simple quadratic function contained with various magnitudes of noise, and DEAS finds local minimum yielding ruggedness measure of given cost function. The proposed shape information will be directly used in improving DEAS performance in future work.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.635-644
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• 2004

A method of identifying structural parameters such as stiffness and damping coefficients at interfacial points of vibro-acoustic systems is suggested using an optimization technique. To identify the parameters using a numerical optimization algorithm, cost functions are defined. The cost function should be zero at the correct parameter values. To minimize the cost functions using an optimization technique, a design sensitivity analysis procedure is developed in the framework of the multi-domain FRF-based substructuring method. As a numerical example, a ladder-like structure problem is introduced. With known parameter values and different initial guesses of the parameters, convergence characteristics to the exact value are compared f3r the three cost functions. Investigating the contours of the cost functions, we find the first cost function has the largest convergent region to the correct value. As another practical problem, stiffnesses of engine mounts and bushings in a passenger car are identified. The numerical examples show that the proposed method is efficient and accurate far realistic problems.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.6
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• pp.536-545
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• 2004

A method of identifying structural parameters such as stiffness and damping coefficients at interfacial points of vibro-acoustic systems is suggested using an optimization technique. To identify the parameters using a numerical optimization algorithm, cost functions are defined. The cost function should be zero at the correct parameter values. To minimize the cost functions using an optimization technique, a design sensitivity analysis procedure is developed in the framework of the multi-domain FRF-based substructuring method. As a numerical example, a ladder-like structure problem is introduced. With known parameter values and different initial guesses of the parameters, convergence characteristics to the exact value are compared for the three cost functions. Investigating the contours of the cost functions, we find the first cost function has the largest convergent region to the correct value. As another practical problem, the stiffnesses of engine mounts and bushings in a passenger car are identified. The numerical examples show that the proposed method is efficient and accurate for realistic problems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.501-509
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• 2003

A method of identifying structural parameters such as stiffness and damping coefficients at interfacial points of vibro-acoustic systems is suggested using an optimization technique. To identify the parameters using a numerical optimization algorithm, cost functions are defined. The cost function should be zero at the correct parameter values. To minimize the cost functions using an optimization technique, a design sensitivity analysis procedure is developed in the framework of the multi-domain FRF-based substructuring method. As a numerical example, a ladder-like structure problem is introduced. With known parameter values and different initial guesses of the parameters, convergence characteristics to the exact value are compared for the three cost functions. Investigating the contours of the cost functions, we find the first cost function has the largest convergent region to the correct value. As another practical problem, stiffnesses of engine mounts and bushings in a passenger car are identified. The numerical examples show that the proposed method is efficient and accurate even when applied to realistic problems.

• Structural Engineering and Mechanics
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• v.59 no.5
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• pp.933-950
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• 2016

Decks, interior beams, edge beams and girders are the parts of a steel floor system. If the deck is optimized without considering beam optimization, finding best result is simple. However, a deck with higher cost may increase the composite action of the beams and decrease the beam cost reducing the total cost. Also different number of floor divisions can improve the total floor cost. Increasing beam capacity by using castellated beams is other efficient method to save the costs. In this study, floor optimization is performed and these three issues are discussed. Floor division number and deck sections are some of the variables. Also for each beam, profile section of the beam, beam cutting depth, cutting angle, spacing between holes and number of filled holes at the ends of castellated beams are other variables. Constraints include the application of stress, stability, deflection and vibration limitations according to the load and resistance factor (LRFD) design. Objective function is the total cost of the floor consisting of the steel profile cost, cutting and welding cost, concrete cost, steel deck cost, shear stud cost and construction costs. Optimization is performed by enhanced colliding body optimization (ECBO), Results show that using castellated beams, selecting a deck with higher price and considering different number of floor divisions can decrease the total cost of the floor.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.357-365
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• 2014

This paper proposed a multi-objective optimization method for building energy system design using primary energy consumption and initial cost. The designing of building energy systems is a complex task, because life cycle cost and efficiency of building are determined by decisions of engineer during the early stage of design. Therefore, methods such as pareto analysis that can generate various alternatives for decision making are necessary. In this study, the optimization is performed using the NSGAII and case study was carried out for feasibility of the proposed method. As a result, alternative solutions can be obtained for the optimal building energy system design.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.8
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• pp.635-640
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• 2006

An optimizer has been applied for the optimal design of pipe diameters in the pipe flow network problems. Pipe network flow analysis, which is developed separately, is performed within the interface for the optimization algorithm. A pipe network is chosen for the test, and optimizer GenOpt is applied with Holder-Mead-O'Niell's simplex algorithm after solving the network flow problem by the Newton-Raphson method. As a result, optimally do-signed pipe diameters are successfully obtained which minimize the total design cost. Design cost of pipe flow network can be considered as the sum of pipe installation cost and pump operation cost. In this study, a practical and efficient solution method for the pipe network optimization is presented. Test system is solved for the demonstration of the present optimization technique.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.468-476
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• 2008

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the $\lambda$-P table method is used to calculate ED for the fitness function of GA. The $\lambda$-P table method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with three kinds of ED problems, namely ED considering valve-point effects (EDVP), ED with multiple fuel units (EDMF), and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all three ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.