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Multiple criteria decision analysis:...
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Chen, Ye.
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Multiple criteria decision analysis: Classification problems and solutions.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Multiple criteria decision analysis: Classification problems and solutions./
作者:
Chen, Ye.
面頁冊數:
183 p.
附註:
Source: Dissertation Abstracts International, Volume: 68-01, Section: B, page: 0603.
Contained By:
Dissertation Abstracts International68-01B.
標題:
Engineering, System Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR23510
ISBN:
9780494235102
Multiple criteria decision analysis: Classification problems and solutions.
Chen, Ye.
Multiple criteria decision analysis: Classification problems and solutions.
- 183 p.
Source: Dissertation Abstracts International, Volume: 68-01, Section: B, page: 0603.
Thesis (Ph.D.)--University of Waterloo (Canada), 2006.
Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are: (1) Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice. (2) Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively. (3) Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM.
ISBN: 9780494235102Subjects--Topical Terms:
1018128
Engineering, System Science.
Multiple criteria decision analysis: Classification problems and solutions.
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Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are: (1) Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice. (2) Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively. (3) Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM.
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Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example.
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Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components.
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A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.
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