Background

Decision making is a systematic and formal process which involves four steps: (i) identification of the problem; (ii) deriving the preferences; (iii) evaluation of alternatives; and (iv) identification of the best alternatives. The domain of decision making involves three kinds of analysis:

1. Descriptive analysis: It extensive involves the decision maker in deriving the inferences from the graphical or tabular presentation of the data/information.
2. Prescriptive analysis: It uses the methods to enabler decision makers for an improved analysis.
3. Normative analysis: It deals with the problems which extensively demand the involvement of decision maker in problem-solving through evaluation of set of arguments trying to present right and wrong about the situation.

It demands crossexamination of the opinions and a consensus need to be sought in arriving at a specific decision. The MCDM techniques discussed in this book are primarily fall into the domain of descriptive and normative analysis. Typically, the techniques in descriptive and normative analysis are considered within the broader domain of operations research (OR).

The purpose of operations research is to enable a quantitative analysis of solving the complex problems in organizational, national or societal domain. OR models are constructed with the help of fundamentals of mathematics, statistics and probability theory to develop optimal solutions. The approaches such as simulation and multicriteria decision making primarily do not look at the optimal solution but intends to analyse various alternatives and scenarios for “what-if” analysis. Typically, OR modelling adopts a simple approach for solving the problems. At the first instance, it tries to break the problem into meaningful and manageable components and then solves it using well-defined theories of mathematics.