Browsing by Author "Teng, JY"

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A multiobjective programming approach for selecting non-independent transportation investment alternatives
(1996-08-01)
Teng, JY
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Tzeng, GH
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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
This article presents a new method for SElecting Non-independent TRansportation investment Alternatives (SENTRA). This method utilizes effective distance heuristic algorithm which attempts to maximize the achieved objectives needed to satisfy available resources. Since transportation investment planning cannot avoid dealing with issues of interdependence among alternatives, this paper will consider four types of investment alternatives: independence, complementarity, substitution and common complementary substitution. Transportation investment alternative selection problem can be formulated in terms of the 0-1 multiobjective multidimensional knapsack problem. Possessing the characteristics of NP-completeness, strict computation is not necessary for the optimal solution, but simple computation for near-optimal solution is expected. The method is proposed in this paper so as to attain the near-optimal solution, which, aside from ranking the selected transportation investment alternatives, can easily perform sensitivity analysis. Finally, an example is presented to illustrate the method. Copyright (C) 1996 Elsevier Science Ltd
Fuzzy multicriteria ranking of urban transportation investment alternatives
(1996)
Teng, JY
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Tzeng, GH
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交大名義發表
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運輸與物流管理系註：原交通所+運管所
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National Chiao Tung University
This paper proposes the fuzzy multicriteria ranking method to conduct the evaluation of urban transportation investment alternatives. Since urban transportation investment is a public investment problem, which requires that various aspects of impacts upon different interest groups be considered, it is therefore regarded as a multicriteria decision making and group decision making problem. In view of future uncertainties, since investment alternatives cannot be cleared in terms of numerical values under the anticipated achievement values of each criterion, it is then considered to be within the range of fuzziness. To make it easier to put the application to practical use, this paper has used triangular fuzzy numbers to spell out the possible range of the anticipated achievement values, whereas the principle of majority rule is used to establish weights and the anticipated achievement values of the triangular fuzzy numbers. From fuzzy weights and fuzzy achievement values, the fuzzy synthetic achievement values of investment alternatives can then be derived. This paper has further revised the Kim-Park method so as to perform the superiority and inferiority comparisons among the fuzzy synthetic achievement values, in the hope that the degree of optimism and pessimism of most of the experts in the decision making group can be demonstrated without each expert stating his/her preferences. An example is used to exemplify the method being presented.
Transportation investment project selection using fuzzy multiobjective programming
(1998-06-16)
Teng, JY
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Tzeng, GH
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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
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.