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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Application of multiple criteria decision making for network improvement
(1997-03-01)
Tzeng, GH
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Tsaur, SH
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
In this paper we propose application of multiple criteria decision making to problems of a metropolitan network improvement plan. Initially, a bilevel multiple objective network design model is considered in two objectives which are minimal government budget and minimal total travel time of road users. We seek feasible improvement alternatives among those bottleneck links in an existing road network structure and travel demand. We present an effective heuristic algorithm to obtain noninferior solutions; then ELECTRE III multiple criteria decision making and group decision making are used to evaluate and to select a compromise solution among those noninferior solutions. From the design phase in multiple criteria decision making, multiple objective mathematical programming is used to formulate a continuous network design model. However, from the phase of evaluation, multiple criteria decision making to solve the discrete network design problem. The network of metropolitan Taipei is taken as an example to illustrate the operation of this model.
Fuzzy bicriteria multi-index transportation problems for coal allocation planning of Taipower
(1996-11-22)
Tzeng, GH
;
Teodorovic, D
;
Hwang, MJ
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Taipower, the official electricity authority of Taiwan, encounters several difficulties in planning annual coal purchase and allocation schedule, e.g., with multiple sources, multiple destinations, multiple coal types, different shipping vessels, and even in uncertain demand and supply. In this study, these concerns are formulated as a fuzzy bicriteria multi-index transportation problem. Furthermore, an effective and interactive algorithm is proposed which combines reducing index method and interactive fuzzy multi-objective linear programming technique to cope with a complicated problem which may be prevalent in other industries. Results obtained in this study clearly demonstrate that this model can not only satisfy more of the actual requirements of the integral system but also offer more information to the decision makers (DMs) for reference in favor of exalting decision making quality.
Transportation investment project selection using fuzzy multiobjective programming
(1998-06-16)
Teng, JY
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Tzeng, GH
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper proposes the fuzzy multiobjective programming for the problem of transportation investment project selection (TIPS). The programming then uses the fuzzy spatial algorithm, which calculates the performance of objective achievement and the requirement of resource utilization as of fuzziness, Under a complex and uncertain decision-making environment, there exists a certain degree of interdependence among these transportation investment projects. This paper uses expert evaluation, and conducts, respectively, with the consensus of most of the experts, the decision on interdependence type (complementary and substitutive) and on the degree of fuzzy interdependence. In every iteration of the fuzzy spatial algorithm, the method of ranking fuzzy numbers must be used so as to obtain the ranking for selecting investment projects. This paper has modified the method provided by Kim and Park in order that the preference of most of the decision makers or experts can be overlooked, since the degree of optimism or pessimism can be demonstrated in the profitability of every investment project. In the end, this paper will employ a numerical example to illustrate the method forwarded. (C) 1998 Elsevier Science B.V. All rights reserved.
A weight-assessing method with habitual domains
(1998-10-16)
Tzeng, GH
;
Chen, TY
;
Wang, JC
;
管理學院
;
College of Management
Weights of criteria are the important factors in decision-making. However, from a behavioral perspective, traditional weighting methods account for too few factors to deal with decisions properly. Based on the behavior mechanism and the theory of habitual domains, this study is undertaken to develop a new weight-assessing model that treats decisionmaking as a dynamically adjusting process proceeding from the ideal to actual states. The new model is built upon the dynamic analysis for the connectivities between criteria instead of the static analysis of traditional models. Finally, we have studied Taipei City motorcycle users, mode-choice behavior through questionnaire in order to show the applicability of the new model. From the empirical results, it is found that our weight-assessing method has significant application potential in practice. (C) 1998 Elsevier Science B.V. All rights reserved.
The optimal location of airport fire stations: A fuzzy multi-objective programming and revised genetic algorithm approach
(1999)
Tzeng, GH
;
Chen, YW
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
As the global aviation business expands rapidly, issues of aviation safety become correspondingly important. In turn, aviation safety should be more emphasized. The crashes of China Airlines planes at Nagoya (Japan) international airport in 1994, and near Taipei's international airport in 1998, caused airport authorities around the world to pay closer attention to rescue and fire-protection plans at their airports. Our research reveals that the location and number of fire stations at an international airport is an important factor in its fire protection capability. However, if the sites of the fire stations are not appropriately planned and located, fire engines and crews cannot arrive at the accident area in a timely manner. Similarly, if the number of fire stations at an airport is not sufficient, fires caused by aircraft accidents may take longer to be extinguished, resulting in more injuries and fatalities. Therefore, a location model based on a fuzzy multi-objective approach is proposed in this paper. This model can help in determining the optimal number and sites of fire stations at an international airport, and can also assist the relevant authorities in drawing up optimal locations for fire stations. Finally, because of the combinatorial complexity of our model, a genetic algorithm (GA) is employed and compared with the enumeration method. The study results show that our revised CA is comparatively effective in resolution and that our model can be applied to the optimal location of other emergency facilities.
A general piecewise necessity regression analysis based on linear programming
(1999-08-01)
Yu, JR
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Tzeng, GH
;
Li, HL
;
運輸與物流管理系註：原交通所+運管所
;
資訊管理與財務金融系註：原資管所+財金所
In possibilistic regression analysis proposed by Tanaka and Ishibuchi (1992), linear programming (LP) formulation of necessity analysis has no feasible solution under the enormous variation of the given data. This work proposes a general piecewise necessity regression analysis based on LP rather than a non-linear interval model that they recommended to obtain the necessity area of the given data. In addition to maintaining a linear property, the proposed method prevents the necessity analysis from having no feasible solution. The problematic univariate example and a multivariate example with respect to different number of change-points are demonstrated by the general piecewise necessity regression. The proposed method characteristic is that, according to data distribution, practitioners can specify the number and the positions of change-points. The proposed method maintains the linear interval model and the order of necessity regression function does not need to be determined. (C) 1999 Elsevier Science B.V. All rights reserved.
A revised minimum spanning table method for optimal expansion of competence sets
(2000)
Chiang, CI
;
Li, JM
;
Tzeng, GH
;
Yu, PL
;
運輸與物流管理系註：原交通所+運管所
Competence set analysis is a new approach to solve an import aspect of challenging MCDM problems. Thus, many researchers have developed efficient methods for solving the optimal expansion of competence sets (please see the references). The minimum spanning table method (MST) proposed by Feng and Yu (1997) is an efficient algorithm using spreadsheet tableaus to solve optimal expansion problems. In order to develop a computer program, in this paper, we propose the revised algorithm of MST, which can efficiently solve the optimal expansion problems. We develop a user-friendly program called MINST, which can solve fairly large-scale expanding problems even with PC of pentium 133.
Fuzzy multi-objective reconstruction plan for post-earthquake road-network by genetic algorithm
(2000)
Tzeng, GH
;
Chen, YW
;
Lin, CY
;
運輸與物流管理系註：原交通所+運管所
;
資訊管理與財務金融系註：原資管所+財金所
According to the seismic experience of Japan and America, earthquakes have often caused damage to the road-networks, which are important for maintaining the quality of life and the daily transit after a disaster. Taiwan and Japan are both located in the Pacific earthquake region, which is very active and unstable. The Taiwanese people will suffer seriously after a large-scale earthquake because the population and road-network are both highly concentrated nowadays. If the necessary reconstruction strategies to cope with quakes are not available, mass travelers can't be efficiently conducted via the post-earthquake road-network. Thus, the convenience of transit after earthquake would be seriously hampered. To aid the reconstruction decision for post-earthquake road-networks, we intend to establish a fuzzy multi-objective model, which is an integration of work scheduling and task assignment for many work-troops. Multiobjective optimization is applied because of the following reasons: first, we do want to minimize the travel-time of travelers during reconstruction; secondly, we intend to minimize total time needed for reconstruction; furthermore, we also expect that each available and homogeneous work-troop on duty will share almost the same work-load during reconstruction. Since the aspiration level of the aforementioned goals are vague, a fuzzy multi-objective approach is used. The algorithm of this combinatorial optimization problem based on a two-step genetic algorithm is then developed and employed to reduce the computation complexity of such a problem. Study results show that a satisfying solution of this problem can be efficiently derived by thirty generations of our modified genetic algorithm- this solution not only instructs the reconstruction order for each damage point in road-network, but also assign the appropriate reconstruction work to relevant work-troops. Thus, for reasons of computational efficiency and practical applicability in this study, we do strongly suggest this research can't only be a basis for seismic simulation but can also be the reference of pre-quake exercises for relevant authorities.
Identification of general fuzzy measures by genetic algorithms based on partial information
(2000-08-01)
Chen, TY
;
Wang, JC
;
Tzeng, GH
;
管理學院
;
College of Management
This study develops an identification procedure for general fuzzy measures using genetic algorithms, In view of the difficulty in data collection in practice, the amount of input data is simplified through a sampling procedure concerning attribute subsets, and the corresponding detail design is adapted to the partial information acquired by the procedure. A specially designed genetic algorithm is proposed for better identification, including the development of the initialization procedure, fitness function, and three genetic operations. To show the applicability of the proposed method, this study simulates a set of experimental data that are representative of several typical classes. The experimental analysis indicates that using genetic algorithms to determine general fuzzy measures can obtain satisfactory results under the framework of partial information.
Using a fuzzy piecewise regression analysis to predict the nonlinear time-series of turbulent flows with automatic change-point detection
(2001)
Tseng, YH
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Durbin, P
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Tzeng, GH
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科技管理研究所
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Institute of Management of Technology
Research has already shown that turbulent flow consists of some coherent time- and space-organized vortical structures. Some dynamic systems and experimental models are employed to understand the turbulent generation mechanism. However, these approaches still cannot provide a good nonlinear analysis of turbulent time-series. In the real turbulent flow, very complicated nonlinear behaviors, which are affected by many vague factors are present. Based on the nonlinear behavior and the results of from this traditional research, we introduce multivariate statistical analysis of an experimental study to explain practical phenomenon. In this paper, a new approach of fuzzy piecewise regression analysis with automatic change-point detection is proposed to predict the nonlinear time-series of turbulent flows. In order to show the practicality and usefulness of this model, we present an example of predicting the near-wall turbulence time-series as a verifiable model. The results of practical applications show that the proposed method is appropriate and appears to be useful in nonlinear analysis and in fuzzy environments to predict the turbulence time-series.

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