Multi-criteria decision methods Flashcards
Uni-criterion vs multi criteria decision models
Uni-criterion model:
– Mathematically well-stated:
• Optimal solution,
• Complete ranking of the actions.
– Socio-economically ill-stated:
• Single criterion? Not realistic.
• Notion of criterion: perception thresholds, …
Multicriteria model: – Mathematically ill-stated: • No optimal solution, • No mathematical meaning. – Socio-economically well-stated: • Closer to real world decision problem, • Search for a compromise solution.
What is Multi-Criteria Decision Analysis (MCDA)
Multi-Criteria Decision Analysis (MCDA) is, ‘‘an umbrella term to describe a collection of formal approaches which seek to take explicit account of multiple criteria in helping individuals or groups explore decisions that matter’’
Three dimensions of MCAM: 1. the formal approach, 2. the presence of multiple criteria, 3. the fact that decisions are made either by individuals or groups of individuals
What are the properties of Multi-Criteria Decision Analysis (MCDA)?
It seeks to take explicit account of multiple, conflicting criteria.
It helps to structure the management problem
it provides a model that can serve as a focus for discussion
it offers a process that leads to rational, justifiable, and explainable decisions.
Moreover:
• it can deal with mixed sets of data, quantitative and qualitative,
including expert opinions.
• it is conveniently structured to enable a collaborative/participative
planning and decision-making environment.
Problem solving steps with MCDM
Intelligence/conceptual phase
- Establish the decision context, the decision objectives (goals), and identify the decision maker(s).
- Identify the alternatives.
- Identify the criteria (attributes) that are relevant to the decision problem
Design phase
4. Assign scores to each alternative per each criterion
5. Standardize/evaluate the raw scores to generate an evaluation or decision
table.
6. Determine a weight for each criterion to reflect how important it is to the
overall decision
Choice phase
7. Use aggregation functions (or decision rules) to compute an overall score
per alternative by combining the weights and standardized scores.
8. Perform a sensitivity analysis to assess the robustness of the preference
ranking to changes in the criteria scores and/or the assigned weights.
What are the criteria characteristics of MCDM?
- Completeness: It is important to ensure that all of the important criteria are
included. - Redundancy: In principle, criteria that have been judged relatively unimportant
or to be duplicates should be removed at a very early stage. - Operationality: It is important that each alternative can be judged against each
criterion. - Mutual independence: Straightforward applications of MCDM require that preferences associated with the consequences of the alternatives are independent of each other from one criterion to the next.
- Number: An excessive number of criteria leads to extra analytical effort in
assessing input data and can make communication of the results of the analysis more difficult.
What is the definition of Multi Criteria Decision Making?
MCDM’s consist of constructing a global preference relation for a set of alternatives evaluated using several criteria.
selection of the best actions from a set of alternatives, each of which is evaluated against multiple, and often conflicting criteria
• A broad set of methods aimed at eliciting and representing the structure of the preferences of the decision maker(s) facing the need to consider multiple objectives and criteria (e.g social, economic and environmental ones):
2 main families of methods:
– MADM
– MODM
What are Multi-Attribute Decision Methods?
Multi-Attribute Decision Methods (MADM): these methods approach problems that are assumed to have a predetermined, limited number of decision alternatives.
What are Multi-Objective Decision Methods?
Multi-Objective Decision Methods (MODM): in this case the decision alternatives are not given, but defined by a set of problem constraints and identified using multiple objective programming. The number of potential decision alternatives may be large, or infinite (optimization methods)
What are the different methods of approaching Economic and integrated appraisal for matters of relevant environmental dimensions?
CBA (cost/benefit analysis): is the preferred approach when full monetization is acceptable and preferred, to support the judgement about a given project or to choose within a set of alternatives;
CEA (cost-effectiveness analysis) can be preferred in those cases in which costs can be quantified in monetary terms, while the environmental dimensions can be assessed by means of nonmonetary indicators. Decisions can be thus framed as the identification of the alternative that meets the environmental objectives at the minimum costs;
MCA (multi-criteria analysis) can be preferred when the economic dimension is only one of the many to be considered, when monetization is challenging or not acceptable and the most
suitable method must be selected within a widest set of possible solutions
What is the WEF security index?
The water, energy and food security nexus according to the Food And Agriculture Organization of the United Nations (FAO), means that water security, energy security and food security are very much linked to one another, meaning that the actions in any one particular area often can have effects in one or both of the others.
What are some water security indicators?
Access to drinking water drought index groundwater depletion index water quality index access to sanitation total internal renewable water resources per capita
What are some energy security indicators?
Aggregated energy availability
aggregated energy affordability
environmental sustainability
social strength
What are some food security indicators?
average food supply Volatility on agricultural production Agricultural Import Tariffs Food loss food consumption protein quality prevalence of obesity
What is a hierarchical multi-criteria evaluation model?
A hierarchical multi-criteria evaluation model was developed to aggregate
indicators first into assessment criteria, then into three indices, and eventually
further aggregated into the final WEF Security Index.
All the indicators have been normalized in order to obtain homogeneous non-dimensional scales between 0 (low security) and 1 (high security). The
normalization procedure was carried out in the GIS environment through fuzzy
membership functions, which were usually linear or in some cases trapezoidal (line and plateau).
Aggregation weights were defined by the authors for demonstration purposes• For the aggregation of the indicators, we used Ordered Weighted Average (OWA) method, whose main feature is the adoption of a second round of weighting applied to the ordered sequence of weighted values to be aggregated.
