• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.9
• /
• pp.304-315
• /
• 2018

Harmony Search (HS) is a recently developed metaheuristic algorithm that is widely known to many researchers. However, due to the increasing complexity of optimization problems, the optimal solution cannot be efficiently found by HS. To overcome this problem, there have been many studies that have improved the performance of HS by modifying the parameter settings and incorporating other metaheuristic algorithms. In this study, Copycat HS (CcHS) is suggested, which improves the parameter setting method and the performance of searching for the optimal solution. To verify the performance of CcHS, the results were compared to those of HS variants with a set of well-known mathematical benchmark problems. The effectiveness of CcHS was proven by finding final solutions that are closer to the global optimum than other algorithms in all problems. To analyze the applicability of CcHS to engineering optimization problems, it was applied to a design problem for Water Distribution Systems (WDS), which is widely applied in previous research. As a result, CcHS proposed the minimum design cost, which was 21.91% cheaper than the cost suggested by simple HS.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.6
• /
• pp.613-622
• /
• 2020

The South Korean government plans for a 37 % reduction in CO2 emissions against business as usual by 2030. Subsequently, the Ministry of Land, Infrastructure and Transport declared a 26.9 % reduction target in greenhouse gas emissions from buildings by 2020 and established the Green Standard for Energy and Environmental Design (G-SEED) to help improve the environmental performance of buildings. Construction companies often work with consulting firms to prepare for G-SEED certification. In the process, owing to inefficient data sharing and work connections, it is difficult to achieve economic efficiency and obtain certification. The objective of this study was to develop an economic model to assist contractors in achieving the required G-SEED scores for materials and resources. To do this, we automated the process for material comparison and selection on the basis of an analysis of actual consulting data, and developed a model that selects material alternatives that can meet the required scores at a minimum cost. Information on materials is input by applying a genetic algorithm to the optimization of alternatives. When the model was applied to actual data, the construction cost could be lowered by 79.3 % compared with existing methods. The economical material selection model is expected to not only reduce construction costs for owners desiring G-SEED certification but also shorten the project design time.

• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.11
• /
• pp.1373-1381
• /
• 1999

이 논문에서는 통신망 설계 응용분야의 문제를 그래프 이론 문제로써 고려해 보았다. 개별 기업체가 서로 떨어진 두 곳을 연결하고자 할 때 공용통신망의 회선을 빌려 통신망을 구축하게 되는데 많은 경우 여러 종류의 회선들이 공급됨으로 어떤 회선을 선택하느냐의 문제가 생긴다. 일반적으로 빠른 회선(low delay)은 느린 회선(high delay)에 비해 비싸다. 그러나 서비스의 질(Quality of Service)이라는 요구사항이 종종 종단지연(end-to-end delay)시간에 의해 결정되므로, 무조건 낮은 가격의 회선만을 사용할 수는 없다. 결국 개별 기업체의 통신망을 위한 통로를 공용 통신망 위에 덮어씌워(overlaying) 구축하는 것의 여부는 두 개의 상반된 인자인 가격과 속도의 조절에 달려 있다. 따라서 일반적인 최소경로 찾기의 변형이라 할 수 있는 다음의 문제가 본 논문의 관심사이다. 두 개의 지점을 연결하는데 종단지연시간의 한계를 만족하면서 최소경비를 갖는 경로에 대한 해결을 위하여, 그래프 채색(coloring) 문제와 최단경로문제를 함께 포함하는 그래프 이론의 문제로 정형화시켜 살펴본다. 배낭문제로의 변환을 통해 이 문제는 {{{{NP-complete임을 증명하였고 {{{{O($\mid$E$\mid$D_0 )시간에 최적값을 주는 의사선형 알고리즘과O($\mid$E$\mid$)시간의 근사 알고리즘을 보였다. 특별한 경우에 대한 {{{{O($\mid$V$\mid$ + $\mid$E$\mid$)시간과 {{{{O($\mid$E$\mid$^2 + $\mid$E$\mid$$\mid$V$\mid$log$\mid$V$\mid$)시간 알고리즘을 보였으며 배낭 문제의 해결책과 유사한 그리디 휴리스틱(greedy heuristic) 알고리즘이 그물 구조(mesh) 그래프 상에서 좋은 결과를 보여주고 있음을 실험을 통해 확인해 보았다.Abstract This paper considers a graph-theoretic problem motivated by a telecommunication network optimization. When a private organization wishes to connect two sites by leasing physical lines from a public telecommunications network, it is often the cases that several categories of lines are available, at different costs. Typically a faster (low delay) lines costs more than a slower (high delay) line. However, low cost lines cannot be used exclusively because the Quality of Service (QoS) requirements often impose a bound on the end-to-end delay. Therefore, overlaying a path on the public network involves two diametrically opposing factors: cost and delay. The following variation of the standard shortest path problem is thus of interest: the shortest route between the two sites that meets a given bound on the end-to-end delay. For this problem we formulate a graph-theoretical problem that has both a shortest path component as well as coloring component. Interestingly, the problem could be formulated as a knapsack problem. We have shown that the general problem is NP-complete. The optimal polynomial-time algorithms for some special cases and one heuristic algorithm for the general problem are described.

• Tunnel and Underground Space
• /
• v.15 no.4 s.57
• /
• pp.264-274
• /
• 2005

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 levels is provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

• Korean Journal of Environmental Biology
• /
• v.39 no.4
• /
• pp.526-535
• /
• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

• The Journal of Engineering Geology
• /
• v.30 no.4
• /
• pp.457-468
• /
• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Magazine of the Korea Concrete Institute
• /
• v.5 no.4
• /
• pp.123-134
• /
• 1993

A rapid progress has been made over last decade in the state-of-the-art earthquake structura1 engineering towards a better understanding of both the earthqauke ground motion and structural response. These efforts seek to ensure that there will be no serious injury or loss of life in the event of earthquake, and that structures can be built at minimum cost. The design of structures in general, concrete structures in particular, to resist strong ground input motions is not a simple matter, and analytical models for such structures must be developed from a design perspective that accounts for the complexities of the structural responses. The primary obj ective of earthquake structural engineering research is to ensure the safety of structures by understanding and improving a design methodology. Ideally, this would require the development of an analytical model related to a design methodology that ensures a ductile performance. For the accurate assessment of the adequacy of analytically developed model, experiments conducted to study the inplane inelastic cyclic behavior of structures should verify the analytical approach. The fundamental goal of this paper is to present and demonstrate experimentally verified analytical methods that provide the adequate degree of safety and confidience in the behavior of reinforced concrete structural components. This study further attempts to extend the developed modeling techruque for use by practicing structural engineers for both the analysis and design.Plication of the relaxed diaphragm through left thoracotomy was done and result was excellent as seen on Fig. 5. Cause of eventration of the left hemidiaphragm was due to paralysis of the left phrenic nerve which was tested during thoracotomy.

• Journal of Korea Water Resources Association
• /
• v.54 no.7
• /
• pp.475-484
• /
• 2021

The optimal design for water distribution system (WDS) is not only satisfying the minimum required water pressure of the nodes, but also minimizing pipe cost, etc. The number of designs of WDS increases exponentially due to the arrangement of various pipes. Various optimization algorithms were applied to propose an optimized design of WDS. In this study, Modified Hybrid Vision Correction Algorithm (MHVCA) with improved self-adapting parameter was applied to optimal design of WDS. The performance was improved by changing the Hybrid Rate (HR) of the existing Hybrid Vision Correction Algorithm (HVCA) to nonlinear HR. To verify the performance of the proposed MHVCA, it applied to mathematical problems consisting of 2 and 30 decision variables and constrained mathematical problems. In order to review the application results of MHVCA, it was compared with Harmony Search (HS), Improved Harmony Search (IHS), Vision Correction Algorithm (VCA) and HVCA. Finally, MHVCA was applied to the optimal design problem of WDS and the results were compared with other algorithms. MHVCA showed better results than other algorithms in mathematical problems and WDS problem. MHVCA will be able to show good results by applying to various water resource engineering problems as well as problems applied in this study.

• Journal of Astronomy and Space Sciences
• /
• v.25 no.2
• /
• pp.181-198
• /
• 2008

Designing satellite constellations providing partial coverage of certain regions becomes more important as small low-altitude satellites receives an increasing attention due to its cost-effectiveness analysis. Generally, Walker's method is a standard constellation method for global coverage but not effective for partial coverage. The purpose of this study is to design optimal constellation of satellites for effective observation in Korean peninsula regions. In this study, a new constellation design method is presented for partial coverage, using direct control of satellites' orbital elements. And also, a ground repeating circular orbit is considered for each satellite's orbit with the Earth oblateness effect. As the results, at least four satellites are required to observe the Korean peninsula regions effectively when minimum elevation angle is assumed as 12 degrees. The results from new method are better than those from the best Walker method. The proposed algorithm will be useful to design satellite constellation missions of Korea in future.

• Journal of the Society of Naval Architects of Korea
• /
• v.49 no.1
• /
• pp.68-78
• /
• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.