A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

Hyde, Kylie; Maier, Holger R.; Colby, C.

doi:10.1016/j.jenvman.2005.06.011

Cited by 98 publications

(55 citation statements)

References 29 publications

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“…Previous research has also found that the priority vector in AHP derived from the eigenvector method can violate a condition of order preservation (Bana E Costa & Vansnick, 2008). Distance-based optimisation plays an important role in deriving criteria weights (Hwang et al, 1981;Hyde, Maier & Colby, 2005;Yu & Lai, 2011). The proposed WLCRT method uses a proximity matrix derived from the distance correlation measures of global scoring relations.…”

Section: Discussionmentioning

confidence: 99%

A weighted linear combination ranking technique for multi-criteria decision analysis

Chou¹

2013

SAJEMS

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Multi-criteria decision analysis (MCDA) is an alternative approach, which provides a way to systematically structure and analyse complex decision problems. This study presents a novel method of applying the weighted linear combination ranking technique (WLCRT) to MCDA. The proposed WLCRT method is based on the linear combinations of matrix algebra calculations. It has distinct advantages in preference modeling, weight elicitation, and aggregation performance. In this method, the decision matrix of preferences is constructed using a 7-point Likert scale. The weights of criteria are elicited from the proximity matrix of preference relations using the eigenvector method. Then, the weighted generalised means are used to aggregate preference information as well as to rank the order of decision alternatives. The WLCRT method can flexibly reflect different decision attitudes for the decision maker. It is both technically valid and practically useful, and can be used in dealing with multiple criteria analysis problems involving ranking of alternatives.

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Section: Discussionmentioning

confidence: 99%

A weighted linear combination ranking technique for multi-criteria decision analysis

Chou¹

2013

SAJEMS

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“…Hyde and Maier [17,18] verified what is the minimum modification of the performances to improve score of the alternative so that it becomes weakly preferred to another alternative. Such result is derived from solving an optimization problem which minimizes the distance between the original and optimized performance values.…”

Section: Review Of Multiple Criteria Sensitivity Analysis Methods Invmentioning

confidence: 96%

Post factum analysis for robust multiple criteria ranking and sorting

et al. 2015

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Providing partial preference information for multiple criteria ranking or sorting problems results in the indetermination of the preference model. Investigating the influence of this indetermination on the suggested recommendation, we may obtain the necessary, possible and extreme results confirmed by, respectively, all, at least one, or the most and least advantageous preference model instances compatible with the input preference information. We propose a framework for answering questions regarding stability of these results. In particular, we are investigating the minimal improvement that warrants feasibility of some currently impossible outcome as well as the maximal deterioration by which some already attainable result still holds. Taking into account the setting of multiple criteria ranking and sorting problems, we consider such questions in view of pairwise preference relations, or attaining some rank, or assignment. The improvement or deterioration of the sort of an alternative is quantified with the change of its performances on particular criteria and/or its comprehensive score. The proposed framework is useful in terms of design, planning, formulating the guidelines, or defining the future performance targets. It is also important for robustness concern because it finds which parts of the recommendation are robust or sensitive with respect to the modification of the alternatives' performance values or scores. Application of the proposed approach is demonstrated on the problem of assessing environmental impact of main European cities.

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“…This is further addressed in Section 3.7 and in the multiple-criteria decision making literature (e.g. Hyde and Maier, 2006;Hyde et al, 2004;Hyde et al, 2005). Additionally, there should be further work on linking the properties of algorithms to the number of objectives, especially with the increasing consideration of larger numbers of objectives when optimising real-world problems.…”

Section: Research Challenges and Future Directionsmentioning

confidence: 99%

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Maier

Kapelan

Kasprzyk

et al. 2014

Environmental Modelling & Software

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532

317

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In all cases accepted manuscripts should:  link to the formal publication via its DOI  bear a CC-BY-NC-ND license -this is easy to do, click here to find out how  if aggregated with other manuscripts, for example in a repository or other site, be shared in alignment with our hosting policy  not be added to or enhanced in any way to appear more like, or to substitute for, the published journal article AbstractThe development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g., model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

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A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

Cited by 98 publications

References 29 publications

A weighted linear combination ranking technique for multi-criteria decision analysis

A weighted linear combination ranking technique for multi-criteria decision analysis

Post factum analysis for robust multiple criteria ranking and sorting

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

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