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Multiple-criteria decision analysis for integrated catchment management [PDF]

Ecological Economics, 2007
Implementation of integrated catchment management (ICM) is hampered by the lack of a conceptual framework for explaining how landowners select farming systems for their properties. Benefit–cost analysis (a procedure that estimates the costs and benefits of alternative actions or policies) has limitations in this regard, which might be overcome by using
Tony Prato, Gamini Herath
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Multiple Criteria Decision Analysis

2014
A probabilistic approach to multicriteria decision problems can take in due account the uncertainty that is inevitably present in preference evaluations. Translating the preference measurements according to different criteria into probabilities of being chosen as the best alternative has two advantages. First, it makes comparable preference evaluations
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Screening in multiple criteria decision analysis

Decision Support Systems, 2008
Screening is a process for multiple criteria decision analysis (MCDA) that reduces a large set of alternatives to a smaller set that most likely contains the best choice. To study screening in detail, MCDA is first interpreted as consequence-based preference aggregation.
Ye Chen, D. Marc Kilgour, Keith W. Hipel
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Multiple Criteria Decision Analysis Software

2016
We provide an updated overview of the state of multiple criteria decision support software. Many methods and approaches have been proposed in the literature to handle multiple criteria decision analysis, and there is an abundance of software that implements or supports many of these approaches.
H. Roland Weistroffer, Yan Li
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Trends in Multiple Criteria Decision Analysis

2010
Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces.- The Need for and Possible Methods of Objective Ranking.- Preference Function Modelling: The Mathematical Foundations of Decision Theory.- Robustness in Multi-criteria Decision Aiding.- Preference Modelling, a Matter of Degree.- Fuzzy Sets and
EHRGOTT M, FIGUEIRA J, GRECO, Salvatore, EDS   +3 more
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Multiple-criteria decisionmaking: A retrospective analysis

IEEE Transactions on Systems, Man, and Cybernetics, 1985
DURING THE PAST two decades the consideration of multiple objectives in modeling and decisionmaking has grown by leaps and bounds. The seventies in particular have seen the emphasis shift from the dominance of single-objective modeling and optimization toward an emphasis on multiple objectives. This has led to the emergence of a new field that has come
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Rough-Set Multiple-Criteria ABC Analysis

2006
Multiple-criteria ABC (MCABC) analysis is conducted using a dominance-based rough set approach. ABC analysis, a well-known technique for inventory planning and control, divides stock-keeping units (SKUs) into three classes according to annual dollar usage.
Ye Chen, Kevin W. Li, Jason Levy, Keith W. Hipel, D. Marc Kilgour   +4 more
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Intrablock Analysis of Designs With Multiple Blocking Criteria

Journal of the American Statistical Association, 1991
Abstract A multidimensional block design (MBD) is an amalgamation of d > 1 component block designs. It may be represented as a d-dimensional lattice with nodes, where b (s) is the number of blocks in the sth component block design. The (j 1, …, jd )-node of the lattice may have h(i, j 1, …, jd ) ≥ 0 experimental units assigned to treatment i, i = 1, …,
Ralph A. Bradley, Frances P. Stewart
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Multiple Criteria Decision Analysis

2001
The field of multiple criteria decision analysis (MCDA) - also sometimes termed multiple criteria decision aid, or multiple criteria decision making (MCDM) - has developed rapidly over the past quarter century and in the process a number of divergent schools of thought have emerged. Multiple Criteria Decision Analysis: An Integrated Approach provides a
Belton, V., Stewart, T.J.
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Heterogeneous Multiple Criteria Group Decision Analysis

2016
The purpose of this chapter is to develop the deviation modeling method to deal with the heterogeneous MCGDM problems with incomplete weight information in which the decision information is expressed as real numbers, interval numbers, linguistic variables, IFNs, HFEs and HFLTSs.
Xiaolu Zhang, Zeshui Xu
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