• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Computers and Concrete
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• v.30 no.2
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• pp.127-141
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• 2022

In this paper, a numerical procedure is proposed for achieving the minimum cost design of reinforced concrete polygonal column cross-sections under compression and biaxial bending. A methodology is developed to integrate the metaheuristic algorithm Quantum Particle Swarm Optimization (QPSO) with an algorithm for the evaluation of the strength of reinforced concrete cross-sections under combined axial load and biaxial bending, according to the design criteria of Brazilian Standard ABNT NBR 6118:2014. The objective function formulation takes into account the costs of concrete, reinforcement, and formwork. The cross-section dimensions, the number and diameter of rebar and the concrete strength are taken as discrete design variables. This methodology is applied to polygonal cross-sections, such as rectangular sections, rectangular hollow sections, and L-shaped cross-sections. To evaluate the efficiency of the methodology, the optimal solutions obtained were compared to results reported by other authors using conventional methods or alternative optimization techniques. An additional study investigates the effect on final costs for an alternative parametrization of rebar positioning on the cross-section. The proposed optimization method proved to be efficient in the search for optimal solutions, presenting consistent results that confirm the importance of using optimization techniques in the design of reinforced concrete structures.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.73-80
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• 2010

The optimal design of water distribution system have started with the least cost design of single objective function using fixed hydraulic variables, eg. fixed water demand and pipe roughness. However, more adequate design is accomplished with considering uncertainties laid on water distribution system such as uncertain future water demands, resulting in successful estimation of real network's behaviors. So, many researchers have suggested a variety of approaches to consider uncertainties in water distribution system using uncertainties quantification methods and the optimal design of multi-objective function is also studied. This paper suggests the new approach of a multi-objective optimization seeking the minimum cost and maximum robustness of the network based on two uncertain variables, nodal demands and pipe roughness uncertainties. Total design procedure consists of two folds: least cost design and final optimal design under uncertainties. The uncertainties of demands and roughness are considered with Latin Hypercube sampling technique with beta probability density functions and multi-objective genetic algorithms (MOGA) is used for the optimization process. The suggested approach is tested in a case study of real network named the New York Tunnels and the applicability of new approach is checked. As the computation time passes, we can check that initial populations, one solution of solutions of multi-objective genetic algorithm, spread to lower right section on the solution space and yield Pareto Optimum solutions building Pareto Front.

• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.213-223
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• 2006

Conventional truss optimization approaches, while often sophisticated and computationally intensive, have been applied to simple, minimum weight-cost models. These approaches do not perform well when applied to real-world trusses, which have costmodels that are complex and which often involve multiple objectives. Thus, this paper describes the optimization strategies that a clustering technique, which identifies members that are likely to have the same product type, uses for the optimal design of truss structures with real- world cost functions that consider the costs on the weight of the truss, the number of products in the design, the number of joints in the structures, and the costs required in the site.At first, the clustering technique is applied to identify the members and to generate a proper initial solution. A simple taboo search technique is then used, which attempts to generate the optimal solution by starting with the solution from the previous technique. For example, the proposed approach is a plied to a typical problem and to a problem similar to relative performances. The results show that this algorithm generates not only better-quality solutions but also more efficient ones

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.315-324
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• 2017

The smart grid with distributed power supply introduces a number of problems including not only the problems of the existing power grid but also the problem of protection co-operation due to new electric phenomenon because it has a mixed operation structure combining the existing radial operation structure and the new loop operation structure. The EMTP based power system analysis method has flexibility and convenience from the view of system configuration but it requires another experimental verification because of uncertainty of design and analysis results. On the other hand, the real demonstration system has difficulties in observing accurate fault on large scale system due to considerable economical and spatial construction cost, system configuration constraint, and it is difficult to demonstrate the distributed, autonomous and adaptive control strategy of smart grid. In this paper, a basic theory for a micro smart grid simulator design using MEMS(Micro Electro-Mechanical Systems) miniaturization technology is studied which can safely and freely experiment and observe electrical phenomena, and distribution, autonomous adaptive control strategy for disturbances on 22.9kV smart grid under minimum economic and spatial cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.479-482
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• 2011

This paper proposes a design of a ship backbone network-based on the survival and efficiency of the ship network. Currently IEC operates the standard ship network, a standard specification "IEC 61162-410 maintains the operation of the network. IEC 61162-410 offers a high stability of the ship network by using terminal equipment. But current studies are incomplete because it has been assumed that the ship's network will operate at double its current capacity. This paper analyzes the double ship backbone topology for an organization and then will summarise the minimum costs required to implement the ship backbone topology using an ILP. Also, we present an effective traffic assignment technique that uses an ILP, metaheuristic, heuristic algorism-based underlying the ship backbone network. The results by experimenting the design of the network confirmed a greter efficiency, stability and cost-effectiveness of the ship network.

• Journal of Distribution Science
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• v.15 no.7
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• pp.35-41
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• 2017

Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

• 지반과기술
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• v.3 no.3
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• pp.15-22
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• 2006

The optimum blasting pattern to excavate a quarry efficiently and economically can be determined based on the minimum production cost, which is generally estimated according to rock fragmentation. Therefore, it is a critical problem to predict fragment size distribution of blasted rocks over an entire quarry. By comparing various prediction models, it can be ascertained that the result obtained from Kuz-Ram model relatively coincides with that of field measurements. Kuz-Ram model uses the concept of rock factor to signify conditions of rock mass such as block size, rock jointing, strength and others. For the evaluation of total production cost, it is imperative to estimate 3-D spatial distribution of rock factor for the entire quarry. In this study, a sequential indicator simulation technique is adopted for estimation of spatial distribution of rock factor due to its higher reproducibility of spatial variability and distribution models than Kriging methods. Further, this can reduce the uncertainty of predictor using distribution information of sample data. The entire quarry is classified into three types of rock mass and optimum blasting pattern is proposed for each type based on 3-D spatial distribution of rock factor. In addition, plane maps of rock factor distribution for each ground level are provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9B
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• pp.569-576
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• 2007

This paper is on the enhancement of our heuristics for GOSST problem that could apply to the design of communication networks offering graduated services. This problem hewn as one of NP-Hard problems finds a network topology meeting the G-Condition with minimum construction cost. In our prior research, we proposed two heuristics. We suggest methods of selecting G-Node and disconnections for Global or Local locating heuristic in this research. The ameliorated Local locating heuristic retrenches 17% more network construction cost saving ratio and the reformed Global locating heuristic does 14% more than our primitives.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.3
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• pp.193-198
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• 2017

This paper discusses the design and control of a switched reluctance motor (SRM) drive system for a built-in car vacuum cleaner. The growing popularity of outdoor activities and recreation has led the automobile industry to expand technologies that increase the convenience of vehicles, and thus, a built-in car vacuum cleaner was introduced. However, the existing DC motor of a vacuum cleaning system has several disadvantages, such as maintenance cost and lifespan issues of its commutator-brush structure. An SRM can be a good alternative to the existing DC motor because of its high-speed capability, long lifespan, low maintenance cost, and high efficiency, among other advantages. A prototype SRM drive is designed and manufactured to verify its feasibility for use in a built-in car vacuum cleaning system. Dynamic simulation is conducted to determine the optimal switching angle for maximum efficiency and minimum torque ripple. Load test, noise measurement, and suction-power tests are also carried out.