• Journal of the military operations research society of Korea
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• v.28 no.2
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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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.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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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.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.1-11
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• 2016

Entani and Tanaka (2007) presented a new approach for obtaining interval evaluations suitable for handling uncertain data. Above all, their approach is characterized by the normalization of interval data and thus the elimination of redundant bounds. Further, interval global weights in AHP are derived by using such normalized interval data. In this paper, we present a heuristic method for finding extreme points of interval data, which basically extends the method by Entani and Tanaka (2007), and also helps to obtain normalized interval data. In the second part of this paper, we show that the solutions to the linear program for interval global weights can be obtained by a simple inspection. In the meantime, the absolute dominance proposed by the authors is extended to pairwise dominance which makes it possible to identify at least more dominated alternatives under the same information.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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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.