Page 289 - DCOM303_DMGT504_OPERATION_RESEARCH

Operations Research

Notes 14.1 Decision-making under Certainty

As we already know, decision theory starts with three fundamental concepts, viz. actions,
conditions and outcomes. While making decisions under certainty, the decision maker is fully
informed, able to compute with perfect accuracy, and fully rational.
Decision under certainty means that each alternative leads to one and only one consequence,
and a choice among alternatives is equivalent to a choice among consequences.

Example: There is only one possible event for the two possible actions: "Do nothing" at
a future cost of $3.00 per unit for 10,000 units, or "rearrange" a facility at a future cost of $2.80 for
the same number of units. A decision matrix (or payoff table) would look as in Table 14.1.

Table 14.1

Actions State of Nature (with probability of 1.0)
Do nothing Rearrange $30,000 (10,000 units $ 3 00)
.


$28,000 (10,000 units $ 2 80)
.
There is only one State of Nature in the matrix because there is only one possible outcome for
each action (with certainty). The decision is obviously to choose the action that will result in the
most desirable outcome (least cost), that is to "rearrange."
Self Assessment

Name the following:

1. Different types of decision-making environment.
2. Discovery or recognition of data that are assembled into an information system.
3. Two most common flaws in decision-making

4. Decision-making environment in which each alternative leads to one and only one
consequence, and a choice among alternatives is equivalent to a choice among consequences.

14.2 Decision Tree Analysis

A decision tree is a decision support tool that uses a tree-like graph or model of decisions and
their possible consequences, including chance event outcomes, resource costs, and utility.
A decision tree is drawn only from left to right, and has only burst nodes (splitting paths) but no
sink nodes (converging paths). Therefore, if drawn manually, it can grow very big and become
hard to draw fully.

A decision tree is used as a visual and analytical tool, where the expected values (or expected
utility) of competing alternatives are calculated.
A decision tree consists of three types of nodes:

1. Decision nodes - commonly represented by squares
2. Chance nodes - represented by circles
3. End nodes - represented by triangles
Decision trees show the possible outcomes of different choices, taking into account probabilities,
costs and returns. They enable a manager to set out the consequences of choices, ensuring that he

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