• 제목/요약/키워드: Multiobjective Programming

검색결과 68건 처리시간 0.019초

다목적 분석 기법을 이용한 상수도 송수계의 펌프와 배수지의 연계 최적 운영 (Application of a Multiobjective Technique for Optimum Operation of Pumps and Reservoirs in Service Water Transmission Systems)

  • 고석구;오민환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.738-743
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    • 1991
  • A multiobjective analysis technique was applied for the optimum operation of pumps and reservoirs in service water transmission systems. Three major objectives were identified and assessed on the normally operating service water transmission systems. They are, 1) stability of pump operation; 2) economic point of view in minimizing the energy cost for pumping; 3) reliability in meeting the stochasticaly varying demands. The measures of these objectives were required times of pump on-offs in stability, required total energy cost in economics, and minimum required storage during the operating horizon in reliability. In order to find the best meeting solution to the decision maker, a set of non-dominated solutions which show the tradeoff relationships between the considering objectives were generated. The DM selects the best solution from this explicit tradeoff relationships using his heuristic decision rules or experience. The theory was verified by applying to the Kumi Service Water System. A combined technique of the ${\varepsilon}-constraint$ and the weighting methods was used to generate the nondominated solutions, and the dynamic programming algorithm was applied to find the optimal solution for the discretized multi-objective analysis problems.

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Goal Programming을 이용한 홍수기 저수지 최적 운영 (Optimal Reservoir Operation Using Goal Programming for Flood Season)

  • 김혜진;안재황;최창원;이재응
    • 한국방재학회 논문집
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    • 제11권2호
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    • pp.147-156
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    • 2011
  • 홍수기 다목적댐 운영의 목적은 홍수조절용량을 최대한 이용하여 하류 주요 지점의 첨두홍수량을 저감시키거나, 계획홍수량을 초과하지 않도록 방류량과 방류시점을 조절함으로써 홍수피해규모를 최소화하는 것이다. 따라서 홍수기 다목적댐 운영에 있어 가장 중요한 것은 최적의 방류시점과 방류량의 결정이며 이를 통해 홍수기말 이수용량을 최대로 확보 하는 점이다. 본 연구에서는 다목적 최적화기법의 하나인 goal programming을 이용하여 홍수기 저수지 최적운영을 실시하였다. goal programming은 선형계획법 또는 비선형계획법을 이용하여 두 개 이상의 목적을 가진 문제의 최적 대안을 구하기 위해, 목표값으로부터의 편차의 합을 최소화하여 최적화하는 기법이다. 홍수기 다목적댐 운영에서 goal programming의 적용성을 검토하기 위해 실제 홍수 사상을 이용하여, 단일저수지 운영과 저수지 연계운영을 실시하였다. 단일저수지 운영을 적용하기 위한 시험유역으로는 충주댐 유역을 선정하였고 저수지 연계운영을 적용하기 위한 시험유역으로는 안동댐과 임하댐 유역을 선정하였다. goal programming의 결과 분석을 위해 저수지 모의운영 모형인 HEC-5 모형의 결과와 비교, 분석하였다. 검토 결과 goal programming을 이용할 경우 홍수기 말에 저수지 수위를 홍수기제한수위로 유지할 수 있었으며 주요 지점의 홍수량을 매 시간 적절히 계획홍수량 아래로 유지할 수 있었다. goal programming을 이용한 최적 운영의 경우 전 구간의 유입량을 알고 있다고 가정한 점에서 실제 저수지 운영과는 차이가 있으나, 적절한 제약조건을 적용하고 홍수예경보를 이용하여 예보된 유입량을 활용하면 최적의 방류량 시점과 방류량을 산정하여 홍수기 다목적댐을 효율적으로 운영할 수 있으며 주요 지점의 홍수량도 저감할 수 있을 것으로 판단된다.

Cost-Traffic Tradeoff를 고려한 통신망 설계의 Clustering 알고리듬 개발 (Development of Clustering Algorithm for the Design of Telecommunication Network Considering Cost-Traffic Tradeoff)

  • 박영준;이홍철;김승권
    • 한국경영과학회지
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    • 제22권3호
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    • pp.23-36
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    • 1997
  • In the design of telecommunication network, the network configuration using hubbing topology is useful for designing and managing the network efficiently : i. e. all of central offices (COs) are grouped into clusters. Each cluster has one hub consisting of large-scale transmission facilities like digital cross-connect systems and ATMs. In clustering process, the community of interest and geographical factor should be considered. However, there exists a tradeoff between two factors. One is to minimize total link costs for geographical factor and the other is to maximize the total intra-cluster traffics for community of interest. Hence, this can be solved by multiobjective linear programming techniques. In this paper, the problem under considerations is formulated as two p-median subproblems taking into considerations total costs and total intra-traffics, respectively. Then we propose the algorithm to solve the problem based on the concept of cost-traffic tradeoff. The algorithm enables to identify efficient cost-traffic tradeoff pairs. An illustration is also presented.

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ON OPTIMALITY AND DUALITY FOR GENERALIZED NONDIFFERENTIABLE FRACTIONAL OPTIMIZATION PROBLEMS

  • Kim, Moon-Hee;Kim, Gwi-Soo
    • 대한수학회논문집
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    • 제25권1호
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    • pp.139-147
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    • 2010
  • A generalized nondifferentiable fractional optimization problem (GFP), which consists of a maximum objective function defined by finite fractional functions with differentiable functions and support functions, and a constraint set defined by differentiable functions, is considered. Recently, Kim et al. [Journal of Optimization Theory and Applications 129 (2006), no. 1, 131-146] proved optimality theorems and duality theorems for a nondifferentiable multiobjective fractional programming problem (MFP), which consists of a vector-valued function whose components are fractional functions with differentiable functions and support functions, and a constraint set defined by differentiable functions. In fact if $\overline{x}$ is a solution of (GFP), then $\overline{x}$ is a weakly efficient solution of (MFP), but the converse may not be true. So, it seems to be not trivial that we apply the approach of Kim et al. to (GFP). However, modifying their approach, we obtain optimality conditions and duality results for (GFP).

에너지기술평가모형에 관한 고찰 (An Overview of Models for Energy Technology Assessment)

  • 김호탁;최기련;강희정;차재호
    • 에너지공학
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    • 제1권1호
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    • pp.111-134
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    • 1992
  • Energy system models have been broadly used for the solution of the assessment of technical and economical characteristics in the national energy systems. The purpose of this study is to overview the structures, potentials and usefulness of system models for energy technology assessment. The conventional models developed so far are not aquate to analyze the energy and environmental problems simultaneously. Energy system models integrated by multiobjective programming are also reviewed and discussed in this paper to judge their usefulness and applicability in simultaneously analyzing the energy and environmental problems.

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데이터 분포특성을 이용한 다목적함수 최적화 알고리즘 개발 (Development of a Multiobjective Optimization Algorithm Using Data Distribution Characteristics)

  • 황인진;박경진
    • 대한기계학회논문집A
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    • 제34권12호
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    • pp.1793-1803
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    • 2010
  • 가중치법이나 목표계획법을 이용하여 다목적함수 최적화를 수행할 때 설계자는 각 함수에 적절한 가중치나 목표값을 설정해 주어야 한다. 하지만 파라미터를 잘못 설정하게 되면 파레토 최적해를 얻지못하기 때문에 이는 설계자에게 큰 부담이 된다. 최근에 데이터의 분포특성만을 이용하여 데이터의 평균과 함수 사이의 거리를 표현하는 마하라노비스 거리(MD)를 최소화하는 MTS기법이 개발되었다. 이 방법은 파라미터를 설정하지 않아도 되는 장점이 있지만 최적해가 참고데이터의 평균으로 수렴하는 단점이 있다. 따라서 본 연구에서는 방향성이 없는 기존의 MD에 방향성을 부여한 새로운 거리 척도인 SMD를 제안하였다. 그리고 SMD법이 계산과정에서 각 함수의 가중치를 자동으로 반영하고 평균에서 가장 멀리 위치한 한 점을 항상 파레토 최적해로 제공한다는 것을 2개의 단순예제를 통해 검증하였다.

다단계 최적화 기법을 이용한 치과용 골내 임플란트의 형상 최적 설계 (Optimum Design of Endosseous Implant in Dentistry by Multilevel Optimization Method)

  • 한중석;서기열;최주호
    • 대한기계학회논문집A
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    • 제27권1호
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    • pp.144-151
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    • 2003
  • In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen fur design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size fur each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem. Favorable solution is obtained by the MLO, which is compared to both solutions made by RSM and sequential quadratic programming (SQP) in the OAO problem.

A MULTIOBJECTIVE MODEL OF WHOLESALER-RETAILERS' PROBLEM VIA GENETIC ALGORITHM

  • MAHAPATRA NIRMAL KUMAR;BHUNIA ASOKE KUMAR;MAITI MANORANJAN
    • Journal of applied mathematics & informatics
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    • 제19권1_2호
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    • pp.397-414
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    • 2005
  • In the existing literature, most of the purchasing models were developed only for retailers problem ignoring the constraint of storage capacity of retailers shop/showroom. In this paper, we have developed a deterministic model of wholesaler-retailers' problem of single product. The storage capacity of wholesaler's warehouse/showroom and retailers' showroom/shop are assumed to be finite. The items are transported from wholesaler's warehouse to retailers' Own Warehouse (OW) in a lot. The customer's demand is assumed to be displayed inventory level dependent. Demands are met from OW and that spaces of OW will immediately be filled by shifting the same amount from the Rented Warehouse (RW) till the RW is empty. The time duration between selling from OW and filling up its space by new ones from RW is negligible. According to relative size of the retailers' existing (own) warehouse capacity and the demand factors, different scenarios are identified. Our objectives are to optimize the cost functions of wholesaler and two retailers separately. To solve this problem, a real coded Genetic Algorithm (GA) with roulette wheel selection/reproduction, whole arithmetic crossover and non-uniform mutation is developed. Finally a numerical example is presented to illustrate the results for different scenarios. To compare the results of GA, Generalised Reduced Gradient Method has been used for the problem. Also, a sensitivity analysis has been performed to study the variations of the optimal average cost with respect to the different parameters.