• Title/Summary/Keyword: 결정론적 최적화 기법

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Reviews of Bus Transit Route Network Design Problem (버스 노선망 설계 문제(BTRNDP)의 고찰)

  • Han, Jong-Hak;Lee, Seung-Jae;Lim, Seong-Su;Kim, Jong-Hyung
    • Journal of Korean Society of Transportation
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    • v.23 no.3 s.81
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    • pp.35-47
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    • 2005
  • This paper is to review a literature concerning Bus Transit Route Network Design(BTRNDP), to describe a future study direction for a systematic application for the BTRNDP. Since a bus transit uses a fixed route, schedule, stop, therefore an approach methodology is different from that of auto network design problem. An approach methodology for BTRNDP is classified by 8 categories: manual & guideline, market analysis, system analytic model. heuristic model. hybrid model. experienced-based model. simulation-based model. mathematical optimization model. In most previous BTRNDP, objective function is to minimize user and operator costs, and constraints on the total operator cost, fleet size and service frequency are common to several previous approach. Transit trip assignment mostly use multi-path trip assignment. Since the search for optimal solution from a large search space of BTRNDP made up by all possible solutions, the mixed combinatorial problem are usually NP-hard. Therefore, previous researches for the BTRNDP use a sequential design process, which is composed of several design steps as follows: the generation of a candidate route set, the route analysis and evaluation process, the selection process of a optimal route set Future study will focus on a development of detailed OD trip table based on bus stop, systematic transit route network evaluation model. updated transit trip assignment technique and advanced solution search algorithm for BTRNDP.

Decision of Storage Coefficient and Concentration Time of Observed Basin Using Nash Model's Structure (Nash 모형의 구조를 이용한 관측유역의 저류상수 및 집중시간 결정)

  • Yoo, Chul-Sang;Shin, Jung-Woo
    • Journal of Korea Water Resources Association
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    • v.43 no.6
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    • pp.559-569
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    • 2010
  • This study proposes an empirical method for estimating the concentration time and storage coefficient of a basin using the Nash unit hydrograph. This method is based on the analytically derived concentration time and storage coefficient of the Nash model. More fundamentally, this method recursively searches convergent number of linear reservoirs and storage coefficient of linear reservoir representing the basin given. This method is to overcome the problem of HEC-HMS to use an optimization technique to estimate the basin concentration time and storage coefficient. The proposed method was applied to the Bangrim station of the Pyungchang river basin, also found to estimate physically reasonable values.

Development and application of long-term reservoir operation rule for single operation (댐의 담독운영을 위한 장기 저수지운영률 도출 및 평가)

  • Kang, Shin-Uk;Lee, Sang-Ho;Kim, Hyeon-Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.233-233
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    • 2011
  • 필요한 수자원을 추가확보하기 위한 댐 건설이 갈수록 어려워짐에 따라 이미 건설된 댐을 최대한 활용하는 과학적 저수지운영 방안이 필요하다. 또한 댐운영자가 쉽게 실무에 적용할 수 있는 방법이어야 한다. 본 연구의 목적은 댐관리자가 이해하기 쉽고 사용하기 쉬운 장기 저수지운영 방안을 개발하고자 하는 것이다. 수위구간별 저수지운영을 위한 운영률을 구성하고 이에 따른 순단위 저수지운영 모형을 구축하였다. 다변량 추계학적 모의발생기법을 사용하여 댐 유입량을 모의 발생하였다. 저수지운영의 수위구간을 결정하기 위한 최적화 방법으로 메타휴리스틱 방법으로 차원변화 탐색기법을 선정하였다. 안동댐의 단독운영을 위한 수위구간별 저수지운영률을 도출하여 저수지 모의운영을 수행하고 기존의 운영실적과 모의결과를 저수지운영 평가기준에 따라 비교하여 평가하였다. 안동댐의 단독운영 결과 모의된 저수위는 실적 저수위보다 전반적으로 높게 유지되었고, 모의 발전량이 실적 발전량보다 평균적으로 높음을 볼 수 있었다. 안동댐의 실적 발전량 평균값은 124.81 GWh이며, 모의결과의 발전량은 131.01 GWh이었다. 모의 발전량이 전반적으로 높은 이유는 방류량이 적은 상황에서 저수위를 높게 유지하여 발전효율을 높게 한 것이 주된 이유라고 사료된다. 안동댐의 실적과 모의 결과를 3 가지 저수지운영 평가기준으로 평가한 결과, 실패한 횟수는 실적이 554 회, 모의결과는 426 회이었다. 또한 2 순 연속하여 실패가 발생한 횟수는 각각 71회, 48 회이었고, 최대 연속 실패는 각각 52 순, 51 순이었다. 또한 총운영 기간에 대한 성공 횟수의 비율을 나타내는 신뢰도는 실적은 0.53, 모의된 결과는 0.64로 약 9 %의 차이를 보였다. 취약도는 실적이 $12.69\times10^6\;m^3$, 모의된 결과가 $5.14\times10^6\;m^3$$7.55\times10^6\;m^3$의 차이를 보였다. 회복도는 실적이 0.21, 모의 결과가 0.13으로 모의결과가 0.08 낮은 것으로 나타났다. 도출된 장기 저수지운영률을 안동댐의 단독운영에 적용한 결과 실적보다 본 연구에서 개발한 방법론에 의한 모의운영이 공급량, 발전량, 저수지 운영평가 통계량에서 나은 결과를 보였다.

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Optimization of Early-phase Ship Design using Set-Based Design and Genetic Algorithm (집합기반설계와 유전자알고리즘을 이용한 초기단계 함정설계 최적화)

  • Park, Jin-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.10
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    • pp.486-492
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    • 2019
  • The system-based approach is needed to select an optimal mix of weapon systems and ship platform among a variety of design alternatives with the uncertainties of the initial required operational capability. In the early-phase design, which included a feasibility study and concept design, it is possible to cause problems when a review of the operational concept, database development, and systematic design are not done, thereby producing uncertain and unstable requirements. To select the best solution without trial-and-error, the U.S. navy has applied the set-based method for the early-phase design of a new ship-to-shore connector. The ship synthesis model plays an important role in applying the set-based method, but only a few countries possess this model and have prohibited this model from being transferred to other countries. This paper suggests a set-based method using a genetic algorithm and decision-making theory through benchmarking existing ship data. The algorithm was verified using the DDG-51 class ship synthesis model to optimize the weapon system design, which has been released for research purposes.

Empirical Approach to Price Modeling in Electricity Market based on Stochastic Process (확률과정론적 기반의 전력시장가격모델링 기법)

  • Kang, Dong-Joo;Kim, Bal-Ho H.
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.24 no.4
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    • pp.95-102
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    • 2010
  • As the electric power industry is evolving into competitive market scheme, a new paradigm is required for the operation of market. Traditional dispatch algorithm was built based on the optimization model with an objective function and multiple constraints. Commercial market simulator followed the concept of the microeconomic model used in the dispatch algorithm, which is called as analytic method. On analytic method it is prerequisite to procure the exact data for the simulation. It is not easy anymore for each market participant to access to other participants' financial information while it used to be easy for monopoly decision maker to know all the information needed for the optimal operation. Considering the changing situation, it is required to introduce a new method for estimating the market price. This paper proposes an empirical method based on stochastic processes expected to build a capacity planning and long term contracts.

Financial Analysis Model Development by Applying Optimization Method in Residential Officetel (최적화 기법을 활용한 주거용 오피스텔 수지분석 모델 개발)

  • Jang, Jun-Ho;Ha, Sun-Geun;Son, Ki-Young;Son, Seung-Hyun
    • Journal of the Korea Institute of Building Construction
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    • v.19 no.1
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    • pp.67-76
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    • 2019
  • The domestic construction industry is changing according to its preference for demand and supply along with urbanization and economic development. Accordingly, initial risk assessments is more important than before. In particular, demand for lease-based investment products such as commercial and office buildings has surged as a substitute for financial products due to low interest rates of banks. Therefore, the objective is to suggest a basic study on financial analysis model development by applying optimization method in residential officetel. To achieve the objective, first, the previous studies are investigated. Second, the causal loop diagram is structured based on the collected data. Third, the system dynamics method is used to develop cost-income simulation and optimization model sequentially. Finally, the developed model was verifed through analyzing a case project. In the future, the proposed model can be helpful whether or not conduct execution of an officetel development project to the decision makers.

MDP(Markov Decision Process) Model for Prediction of Survivor Behavior based on Topographic Information (지형정보 기반 조난자 행동예측을 위한 마코프 의사결정과정 모형)

  • Jinho Son;Suhwan Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.101-114
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    • 2023
  • In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

Two-phases Hybrid Approaches and Partitioning Strategy to Solve Dynamic Commercial Fleet Management Problem Using Real-time Information (실시간 정보기반 동적 화물차량 운용문제의 2단계 하이브리드 해법과 Partitioning Strategy)

  • Kim, Yong-Jin
    • Journal of Korean Society of Transportation
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    • v.22 no.2 s.73
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    • pp.145-154
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    • 2004
  • The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.

Location Analysis of Vocational High Schools' Public Practice Centers in Seoul (서울시의 특성화고등학교 공동실습소 입지 분석)

  • Cho, Seong-Ah;Kim, Sung-Yeun
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.393-403
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    • 2021
  • Recently, there is becoming larger interest in the public practice centers equipped with advanced manufacturing equipment of industries that is difficult to have in all vocational high schools for strengthening practical education and technical education tailored to the Fourth Industrial Revolution in vocational high schools. In this study, using spatial optimization approaches, we explored the optimal location sets of the public practice centers of vocational high schools in Seoul for an illustration. For the proposed optimial location methods, P-median Problem (PMP) and Maximal Coverage Location (MCLP) were used because, when the public practice centers located in priority of large vocational high schools based on the number of students, it showed that the result is not minimizing the travel distance and maximizing the demand of the vocational high school students. This study found that the PMP can find the optimal location sets that minimize the travel distance of whole students. In addition, all students can be captured through locating five public practice centers by MCLP. It should be noted that the optimal locations of this study are limited in Seoul. However, the frame of this methodology applied in this study can be utilized to locate the public practice centers in other regions based on the spatial decision making.

Optimization of Single-stage Mixed Refrigerant LNG Process Considering Inherent Explosion Risks (잠재적 폭발 위험성을 고려한 단단 혼합냉매 LNG 공정의 설계 변수 최적화)

  • Kim, Ik Hyun;Dan, Seungkyu;Cho, Seonghyun;Lee, Gibaek;Yoon, En Sup
    • Korean Chemical Engineering Research
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    • v.52 no.4
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    • pp.467-474
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    • 2014
  • Preliminary design in chemical process furnishes economic feasibility through calculation of both mass balance and energy balance and makes it possible to produce a desired product under the given conditions. Through this design stage, the process possesses unchangeable characteristics, since the materials, reactions, unit configuration, and operating conditions were determined. Unique characteristics could be very economic, but it also implies various potential risk factors as well. Therefore, it becomes extremely important to design process considering both economics and safety by integrating process simulation and quantitative risk analysis during preliminary design stage. The target of this study is LNG liquefaction process. By the simulation using Aspen HYSYS and quantitative risk analysis, the design variables of the process were determined in the way to minimize the inherent explosion risks and operating cost. Instead of the optimization tool of Aspen HYSYS, the optimization was performed by using stochastic optimization algorithm (Covariance Matrix Adaptation-Evolution Strategy, CMA-ES) which was implemented through automation between Aspen HYSYS and Matlab. The research obtained that the important variable to enhance inherent safety was the operation pressure of mixed refrigerant. The inherent risk was able to be reduced about 4~18% by increasing the operating cost about 0.5~10%. As the operating cost increases, the absolute value of risk was decreased as expected, but cost-effectiveness of risk reduction had decreased. Integration of process simulation and quantitative risk analysis made it possible to design inherently safe process, and it is expected to be useful in designing the less risky process since risk factors in the process can be numerically monitored during preliminary process design stage.