Designing Distributed Multi‐Criteria Decision Support Systems for Complex and Uncertain Situations

Wijngaards, Niek J. E.; Schultmann, Frank

doi:10.1002/9781118522516.ch3

Cited by 4 publications

(3 citation statements)

References 95 publications

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“…It is desirable that the aggregation could be obtained applying a simple additive model such as the weighted sum model (WSM). Suppose that j (j = 1, 2, … , J) is an index identifying the failure scenarios, the total performance of the alternative h can be calculated applying Equation (2) [34]:…”

Section: Aggregation Of Many Failure Scenarios With the Weighted Sum Modelmentioning

confidence: 99%

Integrating Cluster Analysis into Multi-Criteria Decision Making for Maintenance Management of Aging Culverts

Marsili

Bödefeld

2021

Mathematics

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Negligence in relation to aging infrastructure systems could have unintended consequences and is therefore associated with a risk. The assessment of the risk of neglecting maintenance provides valuable information for decision making in maintenance management. However, infrastructure systems are interdependent and interconnected systems of systems characterized by hierarchical levels and a multiplicity of failure scenarios. Assessment methodologies are needed that can capture the multidimensional aspect of risk and simplify the risk assessment, while also improving the understanding and interpretation of the results. This paper proposes to integrate the multi-criteria decision analysis with data mining techniques to perform the risk assessment of aging infrastructures. The analysis is characterized by two phases. First, an intra failure scenario risk assessment is performed. Then, the results are aggregated to carry out an inter failure scenario risk assessment. A cluster analysis based on the k-medoids algorithm is applied to reduce the number of alternatives and identify those which dominate the decision problem. The proposed approach is applied to a system of aging culverts of the German waterways network. Results show that the procedure allows to simplify the analysis and improve communication with infrastructure stakeholders.

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Section: Aggregation Of Many Failure Scenarios With the Weighted Sum Modelmentioning

confidence: 99%

Integrating Cluster Analysis into Multi-Criteria Decision Making for Maintenance Management of Aging Culverts

Marsili

Bödefeld

2021

Mathematics

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“…The underlying approaches have been described in Comes () and Comes et al . (, ). The complementary aggregation has been developed to reduce the risk of cognitive biases by enabling the decision makers to have an overview about results of all scenarios.…”

Section: Integration Of Scenarios and Multi‐criteria Decision Analysismentioning

confidence: 99%

“…To determine this small number of scenarios, trade-offs between the gain in information and knowledge and the available resources need to be made. The underlying approaches have been described in Comes (2011) and Comes et al (2012bComes et al ( , 2013. The complementary aggregation has been developed to reduce the risk of cognitive biases by enabling the decision makers to have an overview about results of all scenarios.…”

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confidence: 99%

An Approach to Multi‐Criteria Decision Problems Under Severe Uncertainty

Hiete

Schultmann

2013

Multi Criteria Decision Anal

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Solving complex decision problems is a demanding task; it requires determining and evaluating the consequences of decision alternatives. To this end, uncertain factors that can only partly be influenced by the decision makers, and their interdependencies need to be considered. Scenarios focus on this part of the decision problem; they enable a systematic exploration of a multitude of possible future developments that are relevant for the decision including external events and decisions made. Scenarios are particularly useful when the problem is pervaded by severe uncertainties that cannot be quantified. For the evaluation of alternatives, multiple objectives and the potentially diverging preferences of the involved actors need to be respected. Multi‐criteria decision analysis aims at structuring the problem, evaluating the alternatives and supporting decision makers pursuing multiple goals. We propose an approach integrating scenarios and multi‐criteria decision analysis that focuses on the robustness of alternatives in complex, dynamic, uncertain and time‐bound situations. In this integrated framework, the scenarios provide the basis for evaluating a set of alternatives. Ideally, the set of scenarios considered captures all possible future developments. To appropriately explore this set, formal or analytical approaches to scenario construction generate a large number of scenarios. This challenges the decision makers' information‐processing capacity. To support them in managing the richness of information, a two‐fold approach that uses selection and aggregation is presented. By using a selection method, the scenarios that are deemed most relevant are identified, and their evaluations are presented in detail to decision makers. This approach is complemented by an aggregation of scenario evaluations on the basis of the decision makers' preferences. We present two approaches to facilitate the preference elicitation process. Copyright © 2013 John Wiley & Sons, Ltd.

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A DSS to Assess and Manage the Urban Performances in the Regeneration Plan: The Case Study of Pachino

Trovato

Giuffrida

2014

Computational Science and Its Applications – ICCSA 2014

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Designing Distributed Multi‐Criteria Decision Support Systems for Complex and Uncertain Situations

Cited by 4 publications

References 95 publications

Integrating Cluster Analysis into Multi-Criteria Decision Making for Maintenance Management of Aging Culverts

Integrating Cluster Analysis into Multi-Criteria Decision Making for Maintenance Management of Aging Culverts

An Approach to Multi‐Criteria Decision Problems Under Severe Uncertainty

A DSS to Assess and Manage the Urban Performances in the Regeneration Plan: The Case Study of Pachino

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