完整后设资料纪录
DC 栏位 | 值 | 语言 |
---|---|---|
dc.contributor.author | 邓振源 | en_US |
dc.contributor.author | Teng, Junn-Yuan | en_US |
dc.contributor.author | 曾国雄 | en_US |
dc.contributor.author | Tzeng, Gwo-Hshiung | en_US |
dc.date.accessioned | 2014-12-12T02:09:58Z | - |
dc.date.available | 2014-12-12T02:09:58Z | - |
dc.date.issued | 1991 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#NT803118001 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/56389 | - |
dc.description.abstract | 运输投资计画选择 (TIPS) 问题,先天上具有多目标之本质,同时受到多项资源之限制。在未来不确定性与复杂性下,运输投资规划属于不完整结构问题;因此,当进行运输投资计画选择时,不仅要考虑多目标之本质,同时也要考虑模糊之特性。 运输投资计画之间,常具有相关性,而无法完全视为独立性。本论文将运输投资计画区分为独立类、互补类、替代类、以及同时互补替代类等四类型,再以相关领域之专家,应用非模糊与模糊方法,进行共识性之分类与相关程度之决定。 本论文探讨TIPS问题时,区分为三种情况进行分析,即目标与资源均属非模糊性、目标属模糊性而资源为非模糊性、以及目标与资源均属模糊性等。在达成多个目标与受到多项资源限制下,TIPS问题属于0-1型多目标多次元背包问题,由于具NP完备性之特性,欲求取其最适解将非常困难。鉴此,本论文提出有效之启发式解法……空间效率解法 (spatial efficiency algorithm),以求取近似解,同时将此一解法加以推广至具模糊性之TIPS问题。在模糊空间解法 (fuzzyspatial algorithm)中,需应用模糊数 (fuzzy numbers) 排序之方法;本论文应用Kim-Park排序法,并加以改良,使其不用决策者偏好加入,而又能同时考虑乐观与悲观之程度。 TIPS决策问题,除考虑目标达成之最大化外,对于资源之有效运用亦需同时考量,亦即期望可供使用资源之闲置情形为最小。本论文在运输投资计画之分类与相关程度之决定、TIPS问题三种不同状况之求解、以及模糊数之排序等方面所提出之方法,均利用解释例加以说明。最后,本论文提出未来可行之研究方向,以及在运输投资规划实务上可应用之决策问题。 | zh_TW |
dc.description.abstract | Transportation investment project selection (TIPS) problem, are inherently multiobjective in nature and also subject to multiple resource costraints. Under a situation of uncertainty and complexity in the future, transportation investment planning issues are considered ill-structured. Therefore, when transportation investment planning is performed, not only the multiobjective nature but also the fuzzy characteristics have to be considered. Transportation investment projects are oftentimes characterized by interdependence, which could hardly be seen as independent. This dissertation will classify transportation investment projects into four categories, namely the independent, complementary, substitutive, and common complementary substitutive, and specialist from related expertise will be invited and nonfuzzy and fuzzy methodology will be utilized for deciding consensual classification and degree of interdependence. As this dissertation proceeds to investigate TIPS issues, three types of situations are respectively considered for analysis: objective and resource are both of nonfuzziness, objecive is of fuzziness and resource is of nonfuzziness, objective and resource are both of fuzziness. TIPS issues are of 0-1 multiobjective multidimensional knapsack problem under the condition of achieving multiobjective and being subject to multiple resource constraints, Its inherent trait of NP-completeness further intensifies its difficulty to find the optimal solution, Thus, this dissertation will put forward an effective heuristic algorithm, spatial efficiency algorithm, to obtain the approximate solution, and such algorithm will be extensively applied to TIPS issues of fuzziness. Fuzzy spatial algorithm should utilize the method of ranking fuzzy numbers, and this dissertation will as well apply Kirn-Park method and have it improved so that the preference of decision maker can be overlooked yet the degree of optimism and p-essimism will be taken into account. Aside from seeking the maximization of objective achievement, the decision making of TIPS issues will meanwhile consider the efficient utilization of resources and attempt to attain to minimum idle quantity of available resource. This dissertation will rely on illustrate examples for elucidation as it proceeds to methods presented to decide on the classification and degree of interdependence of transportation investment projets, to come out with solutions to the three situations of TIPS issues, and to rank fuzzy numbers. Finally, some issues for future research and some practical of decision problems on transportation investment planning will be discussed. | en_US |
dc.language.iso | zh_TW | en_US |
dc.subject | 运输 | zh_TW |
dc.subject | 多目标 | zh_TW |
dc.title | 相关性运输投资计画选择之研究—非模糊与模糊多目标规划方法 | zh_TW |
dc.title | Interrelated Transportation Investment Project Selection: A Nonfuzzy and Fuzzy Multiobjective Programming Methodology | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 运输与物流管理学系 | zh_TW |
显示于类别: | Thesis |