Looking for explanations and an example to help illustrate them. I get the basic idea of each question, but I would like something more illustrative to nail down the topics
1. Describe the types of decisions that do not involve uncertainty and risk and common approaches used for analyzing them.
2. Describe how to model decisions involving uncertainty.
3. Explain the components of a decision tree and how optimal decisions are computed.
4. Explain the following terms:
a) calling population
e) queue discipline
5. List and define the major types of performance measures used in queuing analysis.
See the attached file.
Answer 1: Types of Decisions
Decision making is the key skill that managers have to use at the workplace. Managers should have the ability to make good decisions with the available information. A company makes different types of decisions that do not involve uncertainty and risk. In such cases, the decision maker will maximize the return and minimize the cost where he/she knows that outcome is certain. Apart from this, the company also makes decisions to buy the insurance, which will protect the business from future uncertainty. When people make decisions with correct information, full knowledge and experience, such types of decisions do not involve uncertainty and risk. For example, an individual carrying out a pilot study before making decisions. This facilitates the individual to generate accurate results.
There are different types of approaches that can be used to analyze the type of decision making. The probabilistic approach is a method in which the decision maker analyzes the amount of risk that each decision carries (Riabacke, 2006). With the help of this approach, the decision maker can identify which decision does not involve uncertainty and risk and vice versa. For example, in an investment portfolio selection, it is necessary to compare the level of risk in an alternative course of action. The deterministic approach is used in which the decision maker analyzes the result by the outcome alone. For example, a teacher makes the decision whether to promote the student into the next class or not after analyzing their results and if the student will be promoted or not what will be the consequences. Therefore, these approaches are helpful in analyzing the level of uncertainty in particular decisions.
Answer 2: Decision Model involving Uncertainty
In case of decision making under uncertainty, the decision maker cannot estimate the probability of the occurrence of events with each decision alternative. In such a case, three types of decision models are used such as optimistic, conservative and mini-max regret method. With the help of these models, the researcher can make decisions under uncertainty. In the case of the optimistic method, the ...
The solution discusses decisions and queues.