Multicriteria decision-making methods

Triantaphyllou, E. (2000). Multicriteria decision making methods A comparative study. Applied Optimization Series, Kluwer Academic Publishers. 

A detailed discussion of these three common chemometrics methods may be found elsewhere in this Encyclopedia or in compendia such as that by D.L. Massart et al. In general, they provide a backdrop against which the concepts and contributions of the multicriteria decision-making methods (MCDM) may be compared and understood. 

The analytic hierarchy process (AHP), developed by Saaty (1980), is a multicriteria decision making method for ranking alternatives. Using AHP, the DM can assess not only quantitative but also various qualitative factors, such as financial stability, feeling of trust, etc. in the supplier selection process. The buyer establishes a set of evaluation criteria and AHP uses these criteria to rank the different suppliers. AHP can enable the DM to represent the interaction of multiple factors in complex and unstructured situations. AHP does not require the scaling of criteria values. 

Chang P. and Chen Y., (1994), A Fuzzy Multicriteria Decision Making Method for Technology Transfer Strategy Selection in Biotechnology , Fuzzy Sets and Systems, Vol. 63, pp. 131-139. 

Several, but not all, of these mathematical methods (e.g. multicriteria decision making. Chapter 26) or problems (the non-hierarchical clustering methods of Chapter 30, which can be treated as allocation models) have been treated earlier. In this chapter, we will briefly discuss the methods that are relevant to chemo-metricians and have not been treated in earlier chapters yet. 

The Multicriteria Decision Making (MCDM) method that is proposed here [28] is based on the Pareto Optimality (PO) concept, does not make preliminary assumptions about the weighting factors, the various responses are considered explicitly. 

The multicriteria decision making (MCDM) approach is based on methods to rank the studied objects (events, molecules, cases, etc.) on the basis of multiple criteria [Hendriks et al, 1992 Carlson, 1992], In particular, desirability functions and utility functions are multicriteria decision functions able to assign a score to each object on a user-defined tuning. 

Brans, J.P., Mareschal, B., and Vincke, Ph. (1984). PROMETHEE A new family of outranking methods in multicriteria decision making. Operations Research, 84, 477-498. 

The challenge of balancing the many requirements of a successful compound is commonly known as MPO or sometimes multidimensional optimization (MDO), multiobjective optimization (MOOP), or multicriteria decision making (MCDM). For clarity, we will use the term MPO to describe all such methods in this chapter. 

Conducting a BRA requires applying evaluative judgments on the benefit and risk outcomes. A pure mathematical method is not appropriate, but the use of a formal decision-making process involving decision analysis is suitable for and has been applied to the BRA. As the BRA needs to account for multiple benefit and risk criteria, multicriteria decision analysis (MCDA), using a decision-tree model, is appropriate and has been adapted for the BRA to allow for systematic decision making in complex situations. 

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