• Communications for Statistical Applications and Methods
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• 제18권6호
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• pp.817-835
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• 2011

The moment(MM) and least squares(LS) estimations of the parameters are derived for the Pareto distribution in the presence of outliers. Further, we have derived a mixture method(MIX) of estimations with MM and LS that shows that the MIX is more efficient. In the final section we have given an example of actual data from a medical insurance company.

• 한국방재학회 논문집
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• 제11권3호
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• pp.49-56
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• 2011

본 연구는 위험물 수송의 최적경로를 결정하는 방법론을 제안하였다. 위험물 차량의 최적경로를 결정할 때에는 위험도 최소화를 목적으로 하는 공공의 입장과 통행시간 최소화를 목적으로 하는 민간기업의 입장이 서로 상충한다. 본 연구에서는 이러한 다기준 의사결정(Multi-criteria decision making)문제 중 하나인 위험물 수송용 최적경로를 탐색하는 방법론으로 Efficient Vector Labeling(이하 EVL) 알고리즘을 제시하였다. EVL 알고리즘은 위험도와 통행시간을 동시에 고려하여 복수의 Pareto optimal 경로(또는 비지배경로)를 탐색하게 한다. 본 연구는 또한 탐색된 비지배경로간의 중복도를 제어할 수 있도록 설계하였다. 개발된 Efficient Vector Labeling 알고리즘을 Test bed network에 적용하여 기존의 경로탐색 방법론과 비교하였다. 적용 결과 새로운 알고리즘이 기존의 알고리즘보다 합리적인 대안경로를 탐색할 수 있는 것으로 분석되었다.

• 한국비블리아학회지
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• 제31권1호
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• pp.237-255
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• 2020

사회 현상 곳곳에서 나타나고 있는 파레토 법칙(Pareto principle)은 상위 20%가 전체 성과의 80%를 차지한다는 법칙이다. 본 연구에서는 대학도서관 학술정보 공유 협력체에서도 파레토 법칙이 발견되고 있는지 확인하였으며, 더불어 지니계수(Gini coefficient)를 통해 대학 간에 나타나는 학술정보 공유 기여 정도에 대한 격차를 수치로 산출하였다. 그 결과 학술정보 공유 협력 사업에서 상위 20%의 대학도서관이 81.2% 이상의 실적을 주도하고 있었으며, 정보 기여에 대한 격차는 평균 0.78로 매우 심각한 상태를 나타냈다. 대학도서관의 규모를 감안하여 재계산한 지니계수도 일부 사업에서만 균등한 쪽으로 조금 조정되는 양상을 나타냈다. 대학의 형태에 따라서는 전문대학도서관 간의 격차가 4년제 대학도서관보다 극심하였으며, 국립대학도서관보다는 사립대학도서관간의 격차가 더욱 심각한 것으로 나타났다. 마지막으로 도서관의 규모와 학술정보 기여 정도에 따라 참여도서관의 분포를 시각화한 결과, 압도적인 기여 수준을 보이는 대규모 도서관이 존재하였으며, 도서관의 규모는 작지만 상대적으로 높은 기여 수준을 보이는 도서관도 분포하였다.

• Industrial Engineering and Management Systems
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• 제12권2호
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• pp.151-160
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• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권6호
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• 대한조선학회논문집
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• 제42권2호
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• 대한조선학회논문집
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• 제46권4호
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• pp.409-416
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• 2009

The structural design problems are acknowledged to be commonly multi-criteria in nature. The various multi-criteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of a truss and a beam. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

• 수산경영론집
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• 제42권3호
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• pp.31-39
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• 2011

This paper attempts to extend such analysis to the rather more difficult problem of optimal management of transnational fish stocks jointly owned by two countries. Transboundary fish such as Mackerel creates an incentive to harvest fish before a competitor does and leads to over-exploitation. This tendency is especially poignant for transnational stocks since, in the absence of an enforceable, international agreement, there is little or no reason for either government or the fishing industry to promote resource conservation and economic efficiency. In the current paper I examine a game theoretic setting in which cooperative management can provide more benefits than noncooperative management. A dynamic model of Mackerel fishery is combined with Nash's theory of two countries cooperative games. A characteristic function game approach is applied to describe the sharing of the surplus benefits from cooperation and noncooperation. A bioeconomic model was used to compare the economic yield of the optimal strategies for two countries, under joint maximization of net benefits in joint ocean. The results suggest as follows. First, the threat points represent the net benefits for two countries in absence of cooperation. The net benefits to Korea and China in threat points are 2,000 billion won(${\pi}^0_{KO}$) and 1,130 billion won(${\pi}^0_{CH}$). Total benefits are 3,130 billion won. Second, if two countries cooperate one with another, they reach the solution payoffs such as Pareto efficient. The net benefits to Korea and China in Pareto efficient are 2,785 billion won(${\pi}^0_{KO}$) and 1,605 billion won(${\pi}^0_{CH}$) or total benefits of 4,390 billion won : a gain of 1,260 billion won. Third, the different price effects under the two scenarios show that total benefit rise as price increases.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2005년도 추계학술대회 논문집
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• pp.306-309
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• 2005

We consider the multi-objective optimization of a multi-service arrayed-waveguide grating-based single-hop metro WDM network with the two conflicting objectives of maximizing throughput while minimizing delay. We develop and evaluate a genetic algorithm based methodology for finding the optimal throughput-delay tradeoff curve, the so-called Pareto-optimal frontier. Our methodology provides the network architecture and the Medium Access Control protocol parameters that achieve the Pareto-optima in a computationally efficient manner. The numerical results obtained with our methodology provide the Pareto-optimal network planning and operation solution for a wide range of traffic scenarios. The presented methodology is applicable to other networks with a similar throughput-delay tradeoff.

• 산업공학
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• 제21권1호
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• pp.75-84
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• 2008

It is a difficult task for decision makers(DMs) to choose an appropriate release plan which balances the conflicts between water storage and hydro-electric energy generation in a multi-reservoir operation problem. In this study, we proposed a DEA-based ranking procedure by which the DM can rank the potential alternatives and select the best solution among the Pareto-optimal solutions. The proposed procedure can resolve the problem of mix inefficiency that may cause errors in measuring the efficiency of alternatives. We applied the proposed procedure to the multi-reservoir operation problem for the Geum-River basin and could choose the best efficient solution from the Pareto-set which were generated by the Coordinated Multi-Reservoir Operating Model.