The Decision Making With Multiple Criteria

This paper looks at the main issues faced by decision makers, analyses them, presents alternatives and makes recommendations based on the analysis.

Provide a description of a scenario in which this kind of decision between two choices, based on weighing their underlying attributes, applies in the “real-world” business setting. Furthermore, what are the benefits and drawbacks, if any, to this method of decision making?

Identifying the decision criteria and allocating weights to the criteria are components of the specific plans within the planning process. Identifying what is relevant to the purchase and giving each priority the correct weight helped the plan to come to fruition. Every element of the process must be specified so that the best decision will be made.

The standard definition of decision making is; the process of mapping the likely consequences of decisions, working out the importance of individual factors and choosing the best course of action to take ("Definition of decision,"). In this case study effective decision making tools will be used to choose the best course of action to take in the scenario.

Decision analysis is an integral and powerful component in the decision making process, and can be used to determine the optimal decision alternative according to the criterion set by the business by objectively assessing the complicating factors and underlying issues of each decision. In this case study, the analysis of the problems faced by Oceanview Development Corporation will start off with a decision tree

There are different methods to solve multi-criteria decision-making problems. Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are two methods introduced by Tomas Saaty. AHP tries to solve the decision problem by modeling it in a hierarchy while ANP is used when the problem is so complex that cannot be modeled as a hierarchy. This complexity occurs because of the effect of criteria on each other or the effect of alternatives on criteria. The Analytic Network Process is a generalization of the Analytic Hierarchy Process. ANP approach comprises four steps [87]:

Decision analysis has been used in almost every industry. In some areas with more success than in the others but generally we can claim that there is hardly any field of life which has not made use of it. Some areas where these techniques worked well are petroleum, pharmaceuticals and electric power industries (Howard 2007).

Decision tree analysis known as an analytical tool applied to decision-making under condition of uncertainty, also clarifying where there are many possible outcomes for various alternatives and some outcomes are dependent on previous outcomes. However, decision tree will present as a diagram by showing the relationship among possible courses of action, possible events and the potential outcomes for each course of action in the decision (Drury, 2012). So decision tree analysis is useful for merchant navy company to understand in what direction their chance events are and what their values in terms of profits and losses are for each of the two tooling alternatives, also visualize the outcomes of different prospects

There are several methods to solve multi-criteria decision-making problems. Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are two methods created by Tomas Saaty. AHP endeavor to solve the decision making problem by formed it in a hierarchy while ANP is used when the problem is so complex that cannot be formed as a hierarchy. This complexity happens because of the effect of criteria between each other or the effect of alternatives on criteria. Generally we can say The Analytic Network Process is a generalization of the Analytic Hierarchy Process. The ANP approach can be comprises in to four steps [87]:

It is fairly difficult to define precisely the word decision but everybody agrees to have experienced the concept. Every human being thinks, rightly or wrongly, that in many occasions he has made a choice between different alternatives. The natural notion of human free will in choosing between various alternatives will be discussed in my paper. On the other hand, Ai (Artificial Intelligence) is the ability of a machine to think or act humanly or rationally. There are at least two basic views about AI. The first one states AI as ‘sciences of the artificial’ (Simon, 1969), or the science of developing machines performing human tasks. The view of AI has relatively few link with decision making to the extent that a machine cannot make a decision until and unless it has been programmed to do so. In other words, the concept of

In our everyday life we are in front of multiple decisions to take, from the easy ones as what coffee to get to the more complicated ones, as what jobs to apply for. The word ‘Decision’ originated from Latin word ‘de ciso’ which indicates ‘cutting off’. This implicates that the act of deciding is to come to a conclusion among different options. How many options are available though? Throughout the years, many behavioural scientists proposed different theories in order to explain how we face decisions and act before them. Do we calculate them all accurately before ‘cutting off’? One of the most recognized theories for decision making is the von Neumann- Morgenstern utility theorem (1944), which states that the decision-maker in front of all the different choices will behave as if he is maximizing the expected value of some function defined over the potential outcomes. Based on the expected utility, the von Neumann-Morgenstern model is constructed upon the fundamental assumption that humans behave in a perfect rational way being able to calculate all the options and choosing among them the one that allows to maximize the expected utility. However, as the major critics to this model sustain, individuals are not fully rational when taking decisions. Their cognitive process is limited to the complexity of the environment in which they are taking decisions. The homo economicus is portrayed as capable of solving complex problems of optimization of resources allocation as well as

I don’t make any decisions just by considering few parts. I usually make decisions based on a complete picture and the final result that the decision can provide to me. For example, the recent decision made by me in buying a laptop illustrates this clearly. Even though I am not interested in playing games and using heavy software, I was motivated to buy a laptop with an advanced processor and graphics card. This is where one of the descriptive decision making comes into play i.e.., “Holistic evaluation”.

The next section reviews the three anomalies of multi-alternative decision making. Then we illustrate how the three theories mentioned above explain the anomalies. After that, the decision field theory is compared with the other two models respectively.

The analytical hierarchy process was created by Saaty to add constraints into the LAP so that it is a global problem. Since the global scale required additional regulations such as; political situations, global competition, government regulations, and economic factors are added. This hierarchy is created to be able to give a swift answer in a political environment where time is of the essence. The first thing that must be established in the hierarchy is the goal, then the criteria, and lastly the alternative locations. This problem requires the decision makers to apply weights to certain goals and locations. The decision maker(s) have to place a weight or priority on each of the alternatives the criteria creates. The weighing is given by equation 1 below.

This method is use to rank the different sets of ACA. It consists of set weighted criteria up on which the potential actions can be scored and sums to gain the total score and average. Based on this it could determine which among the options is the best and suitable for the case situation