• Title/Summary/Keyword: Optimal deployment

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Deployment Strategy of ARGO Floats in the East Sea (동해 ARGO 플로트의 투하 전략)

  • Park, Jong Jin;Park, Jong Sook
    • Ocean and Polar Research
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    • v.37 no.3
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    • pp.179-188
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    • 2015
  • This study was carried out to determine the optimal number of ARGO floats in the East Sea in order to maximize their applications. The dominant spatio-temporal scale, size of the domain, and the typical float lifetimes in the East Sea were taken into consideration. The mean spatial de-correlation scale of temperature on isobaric surfaces reaches about 60 km. The minimum necessary number of floats is about 82 on average in order to secure independent ARGO profiles with the de-correlation scale. Considering the float lifetimes, about 27 floats per year should be deployed to maintain the 82 ARGO float array every year. To obtain spatially uniform distribution of ARGO float data, mean residence time and dispersion rate (basin area/residence time) of ARGO floats were evaluated in each basin of the East Sea. A faster (slower) dispersion rate requires more (less) ARGO floats to maintain the spatially uniform number of floats. According to the analysis, it is likely that the optimal ratio of the number of floats for each basin is 1:2:4 corresponding to Ulleung Basin:Yamato Basin:Japan Basin. In order to maintain relatively uniform ARGO observing networks, it is necessary to establish a long-term plan for deployment strategy based on float pathways and the dispersion rate parameters estimated by using currently active ARGO float trajectory data as well as reanalysis data.

A Study on an Optimal Requirement and Allocation Planning of Emergency Service Facilities (긴급서어비스 시설의 적정소요 및 배분)

  • Hwang, Hak;Hwang, Heung-Seok;Chung, Ho-Won
    • Journal of the Korean Operations Research and Management Science Society
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    • v.6 no.1
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    • pp.75-82
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    • 1981
  • This paper considers urban emergency service systems that dispatch vehicles (facilities) from fixed bases with the objective of finding an optimum allocation of emergency facilities. A case study of fire station problem of Seoul city is conducted to analyze the deployment of fire-fighting resources and develop a class of improved deployment strategies with Parameteric Allocation Model (P.A.M.). The study shows a long term plan leading to balanced fire protection for most fire hazardous districts as well as low alarm districts.

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Dynamic Programming Approach for Determining Optimal Levels of Technical Attributes in QFD under Multi-Segment Market (다수의 개별시장 하에서 QFD의 기술속성의 최적 값을 결정하기 위한 동적 계획법)

  • Yoo, Jaewook
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.2
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    • pp.120-128
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    • 2015
  • Quality function deployment (QFD) is a useful method in product design and development to maximize customer satisfaction. In the QFD, the technical attributes (TAs) affecting the product performance are identified, and product performance is improved to optimize customer requirements (CRs). For product development, determining the optimal levels of TAs is crucial during QFD optimization. Many optimization methods have been proposed to obtain the optimal levels of TAs in QFD. In these studies, the levels of TAs are assumed to be continuous while they are often taken as discrete in real world application. Another assumption in QFD optimization is that the requirements of the heterogeneous customers can be generalized and hence only one house of quality (HoQ) is used to connect with CRs. However, customers often have various requirements and preferences on a product. Therefore, a product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. To overcome these problems, this paper proposes an optimization approach to find the optimal set of TAs under multi-segment market. Dynamic Programming (DP) methodology is developed to maximize the overall customer satisfaction for the market considering the weights of importance of different segments. Finally, a case study is provided for illustrating the proposed optimization approach.

On an Optimal Artillery Deployment Plan (포대의 적정배치 방안)

  • Yun, Yun-Sang;Kim, Seong-Sik
    • Journal of the military operations research society of Korea
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    • v.8 no.2
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    • pp.17-30
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    • 1982
  • This paper offers an optimal artillery deployment scheme for the defending unit when two forces are confronted at a military front line. When proposed gun sites, types and number of guns as well as targets are given, the solutions of the two models in this paper direct each (unit of) guns to a certain location. The aim of the models is to maximize the number of guns which can hit important targets. Unlike widely used target assignment models, these models are formulated using the set covering problem concept. These models do not contain probabilities and time. Thus they are simple as models, easy in implementation, and yield tractable solutions. The dynamic and probabilistic feature of battle situations is implicitly reflected on the models. The first model is for the case that enemies' approaching route is clearly predictable, while the second model is for the unpredictable approaching route case.

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Service Deployment and Priority Optimization for Multiple Service-Oriented Applications in the Cloud (클라우드에서 서비스 지향 응용을 위한 최적 서비스 배치와 우선순위 결정 기법)

  • Kim, Kilhwan;Keum, Changsup;Bae, Hyun Joo
    • Journal of Information Technology Services
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    • v.13 no.3
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    • pp.201-219
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    • 2014
  • This paper considers service deployment and priority optimization for multiple service-oriented applications sharing reusable services, which are deployed as multiple instances in the cloud. In order to handle variations in the workloads of the multiple applications, service instances of the individual reusable services are dynamically provisioned in the cloud. Also service priorities for each application in a particular reusable service are dynamically adjusted. In this paper, we propose an analytic performance model, based on a queueing network model, to predict the expected sojourn times of multiple service-oriented applications, given the number of service instances and priority disciplines in individual reusable services. We also propose a simple heuristic algorithm to search an optimal number of service instances in the cloud and service priority disciplines for each application in individual reusable services. A numerical example is also presented to demonstrate the applicability of the proposed performance model and algorithm to the proposed optimal decision problem.

Optimal Design of Stiffness of Torsion Spring Hinge Considering the Deployment Performance of Large Scale SAR Antenna (전개성능을 고려한 대형 전개형 SAR 안테나의 회전스프링 힌지의 강성 최적설계)

  • Kim, Dong-Yeon;Lim, Jae Hyuk;Jang, Tae-Seong;Cha, Won Ho;Lee, So-Jeong;Oh, Hyun-Ung;Kim, Kyung-Won
    • Journal of Aerospace System Engineering
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    • v.13 no.3
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    • pp.78-86
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    • 2019
  • This paper describes the stiffness optimization of the torsion spring hinge of the large SAR antenna considering the deployment performance. A large SAR antenna is folded in a launch environment and then unfolded when performing a mission in orbit. Under these conditions, it is very important to find the proper stiffness of the torsion spring hinge so that the antenna panels can be deployed with minimal impact in a given time. If the torsion spring stiffness is high, a large impact load at the time of full deployment damages the structure. If it is weak, it cannot guarantee full deployment due to the deployment resistance. A multi-body dynamics analysis model was developed to solve this problem using RecurDyn and the development performance were predicted in terms of: development time, latching force, and torque margin through deployment analysis. In order to find the optimum torsion spring stiffness, the deployment performance was approximated by the response surface method (RSM) and the optimal design was performed to derive the appropriate stiffness value of the rotating springs.

The Optimal Deployment Problem of Air Defense Artillery for Missile Defense (미사일 방어를 위한 방공포대 최적 배치 문제)

  • Kim, Jae-Kwon;Seol, Hyeonju
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.39 no.1
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    • pp.98-104
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    • 2016
  • With the development of modern science and technology, weapon systems such as tanks, submarines, combat planes, radar are also dramatically advanced. Among these weapon systems, the ballistic missile, one of the asymmetric forces, could be considered as a very economical means to attack the core facilities of the other country in order to achieve the strategic goals of the country during the war. Because of the current ballistic missile threat from the North Korea, establishing a missile defense (MD) system becomes one of the major national defense issues. This study focused on the optimization of air defense artillery units' deployment for effective ballistic missile defense. To optimize the deployment of the units, firstly this study examined the possibility of defense, according to the presence of orbital coordinates of ballistic missiles in the limited defense range of air defense artillery units. This constraint on the defense range is originated from the characteristics of anti-ballistic missiles (ABMs) such as PATRIOT. Secondly, this study proposed the optimized mathematical model considering the total covering problem of binary integer programming, as an optimal deployment of air defense artillery units for defending every core defense facility with the least number of such units. Finally, numerical experiments were conducted to show how the suggested approach works. Assuming the current state of the Korean peninsula, the study arbitrarily set ballistic missile bases of the North Korea and core defense facilities of the South Korea. Under these conditions, numerical experiments were executed by utilizing MATLAB R2010a of the MathWorks, Inc.

An Optimal Container Deployment Policy in Fog Computing Environments (Fog Computing 환경에서의 최적화된 컨테이너 배포 정책)

  • Jin, Sunggeun;Chun, In-Geol
    • Journal of Korea Society of Industrial Information Systems
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    • v.26 no.3
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    • pp.1-7
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    • 2021
  • Appropriate containers are deployed to cope with new request arrivals at Fog Computing (FC) hosts. In the case, we can consider two scenarios: (1) the requests may be queued until sufficient resources are prepared for the container deployments; (2) FC hosts may transfer arrived service requests to nearby FC hosts when they cannot accommodate new container deployments due to their limited or insufficient resources. Herein, for more employed neighboring FC hosts, arrived service requests may experience shorter waiting time in container deployment queue of each FC host. In contrast, they may take longer transfer time to pass through increased number of FC hosts. For this reason, there exists a trade-off relationship in the container deployment time depending on the number of employed FC hosts accommodating service request arrivals. Consequently, we numerically analyze the trade-off relationship to employ optimal number of neighboring FC hosts.

A Genetic Algorithm for Solving a QFD(Quality Function Deployment) Optimization Problem

  • Yoo, Jaewook
    • International Journal of Contents
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    • v.16 no.4
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    • pp.26-38
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    • 2020
  • Determining the optimal levels of the technical attributes (TAs) of a product to achieve a high level of customer satisfaction is the main activity in the planning process for quality function deployment (QFD). In real applications, the number of customer requirements for developing a single product is quite large, and the number of converted TAs is also high so the size of the house of quality (HoQ) becomes huge. Furthermore, the TA levels are often discrete instead of continuous and the product market can be divided into several market segments corresponding to the number of HoQ, which also unacceptably increases the size of the QFD optimization problem and the time spent on making decisions. This paper proposed a genetic algorithm (GA) solution approach to finding the optimum set of TAs in QFD in the above situation. A numerical example is provided for illustrating the proposed approach. To assess the computational performance of the GA, tests were performed on problems of various sizes using a fractional factorial design.

Optimal Allocation of Mobilization Designee by Out of Kilter Method (Out of Kilter법을 이용한 동원병력 최적할당에 관한 연구)

  • An Dae-Hui;Kim Chung-Yeong
    • Journal of the military operations research society of Korea
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    • v.17 no.2
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    • pp.54-71
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    • 1991
  • It is very important to increase defence capability rapidly against any surprise attack. This can be done by fast deployment of mobilization reserved resources. This paper is forcused on optimal allocation of special reserved resources. First of all, the location of special reserved resources is identified and then the location of combat and mobilization units and amount of requirement resources of each unit are identified. Finally, optimal allocation of the special reserved resources is obtained by Out of Kilter method.

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