• 한국국방경영분석학회지
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• 제28권2호
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• pp.34-55
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• 2002

This paper deals with the multiple attribute decision making problem when a decision maker incompletely articulates his/her preferences about the attribute weight and alternative value. Furthermore, we consider the attribute tree which is structured hierarchically. Techniques for establishing dominance with linear partial information are proposed in a hierarchically structured attribute tree. The linear additive value function under certainty is used in the model. The incompletely specified information constructs a feasible region of linear constraints and therefore the pairwise dominance relationship between alternatives leads to intractable non-linear programming. Hence, we propose solution techniques to handle this difficulty. Also, to handle the tree structure, we break down the attribute tree into sub-trees. Due to there cursive structure of the solution technique, the optimization results from sub-trees can be utilized in computing the value interval on the topmost attribute. The value intervals computed by the proposed solution techniques can be used to establishing the pairwise dominance relation between alternatives. In this paper, pairwise dominance relation will be represented as strict dominance and weak dominance, which ware already defined in earlier researches.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.479-482
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• 2004

This paper proposes a new framework for variability analysis in QFD. The proposed framework considers the uncertainty of the information contained in the house of quality chart and analyzes the variability resulting in the outcome. A new framework provides a dominance index and a difference index for each pairwise ECs. The indices are helpful to evaluate priorities of each pairwise EC.

• 한국경영과학회지
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• 제23권3호
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• pp.63-73
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• 1998

The paper deals with interactive multiple criteria decision making procedure when decision maker (DM) specifies her or his preference in incomplete ways. Usually DM is willing or able to provide only incomplete information, because of time pressure and lack of knowledge or data. Under incomplete information on utility and attribute weight, the pairwise dominance checks result in strict or weak dominance values. Considering only strict dominance values sometimes fails to Prioritize alternatives because of fuzziness of preference information. Further there exists some information loss useful if used, otherwise. In this paper, we consider the outranking concept which implies the willingness of DM's taking some risk under the least favorable situation because she has enough reasons to admit the results. By comparing the magnitude of net preference degree of alternatives which is defined by difference between outrankings and outranked degree of each alternative, we can prioritize alternatives.

• 지능정보연구
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• 제22권2호
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• pp.1-11
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• 2016

Entani and Tanaka(2007)는 불확실한 데이터를 처리하기에 적합한 구간 평가결과를 얻는 새로운 방법을 제시하였다. 무엇보다 그들의 방법은 구간 데이터를 정규화하여 redundant 데이터를 제거하는데 특징이 있다. 더 나가 정규화된 구간데이터를 활용하여 계층분석과정(AHP)에서 최종 구간 우선순위벡터를 도출한다. 이 논문에서는 구간 데이터의 정규화 목적을 달성하기 위해 구간 데이터의 꼭지점을 구하는 쉽고 간편한 휴리스틱 방법을 제시한다. 한편 간단한 검사법을 활용하여 정규화된 데이터를 활용하여 최종 구간 우선순위벡터를 도출하는 방법을 제시하고자 한다. 아울러 Entani and Tanaka(2007)가 제시한 대안간 지배관계 규명 방법을 확장한 지배관계 규명 방법을 제시하고자 한다.

• 한국경영과학회지
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• 제23권3호
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• pp.27-36
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• 1998

This work has improved the method of Kim and Gal's (6) in that of requiring less response of the DM(decision maker) and ease of reply. The underlying notion is the MCDC(maximally changeable dominance cone) for describing all efficient solutions under the particular preference structure. According to the DM's partial preference expression, enlarging the MCDC is achieved, which results in reducing the solutions needed to take into consideration. The cone generators corresponding to the DM's response are added to the MCDC, which results the MCDC is enlarged. Adopting the scheme of pairwise comparison as a means of acquiring preference attitude, an improved interactive method is proposed. And also, a scheme of choosing a reference point is suggested to achieve the computational efficiency.

• 산업경영시스템학회지
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• 제38권3호
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.