Skip to main content

Fuzzy Logic - Decision Making

It is an activity which includes the steps to be taken for choosing a suitable alternative from those that are needed for realizing a certain goal.

Steps for Decision Making

Let us now discuss the steps involved in the decision making process −

  • Determining the Set of Alternatives − In this step, the alternatives from which the decision has to be taken must be determined.

  • Evaluating Alternative − Here, the alternatives must be evaluated so that the decision can be taken about one of the alternatives.

  • Comparison between Alternatives − In this step, a comparison between the evaluated alternatives is done.

Types of Decision

Making We will now understand the different types of decision making.

Individual Decision Making

In this type of decision making, only a single person is responsible for taking decisions. The decision making model in this kind can be characterized as −

  • Set of possible actions

  • Set of goals Gi(i∈Xn);

  • Set of Constraints Cj(j∈Xm)

The goals and constraints stated above are expressed in terms of fuzzy sets.

Now consider a set A. Then, the goal and constraints for this set are given by −

Gi(a) = composition[Gi(a)] = Gi1(Gi(a)) with Gi1

Cj(a) = composition[Cj(a)] = Cj1(Cj(a)) with Cj1 for a∈A

The fuzzy decision in the above case is given by −

FD=min[i∈XninfGi(a),j∈XminfCj(a)]

Multi-person Decision Making

Decision making in this case includes several persons so that the expert knowledge from various persons is utilized to make decisions.

Calculation for this can be given as follows −

Number of persons preferring xi to xj = N(xi,xj)

Total number of decision makers = n

Then, SC(xi,xj)=N(xi,xj)n

Multi-objective Decision Making

Multi-objective decision making occurs when there are several objectives to be realized. There are following two issues in this type of decision making −

  • To acquire proper information related to the satisfaction of the objectives by various alternatives.

  • To weigh the relative importance of each objective.

Mathematically we can define a universe of n alternatives as −

A=[a1,a2,...,ai,...,an]

And the set of “m” objectives as O=[o1,o2,...,oi,...,on]

Multi-attribute Decision Making

Multi-attribute decision making takes place when the evaluation of alternatives can be carried out based on several attributes of the object. The attributes can be numerical data, linguistic data and qualitative data.

Mathematically, the multi-attribute evaluation is carried out on the basis of linear equation as follows −



Anurag Rana

Comments

Post a Comment

Popular posts from this blog

Standard and Formatted Input / Output in C++

The C++ standard libraries provide an extensive set of input/output capabilities which we will see in subsequent chapters. This chapter will discuss very basic and most common I/O operations required for C++ programming. C++ I/O occurs in streams, which are sequences of bytes. If bytes flow from a device like a keyboard, a disk drive, or a network connection etc. to main memory, this is called   input operation   and if bytes flow from main memory to a device like a display screen, a printer, a disk drive, or a network connection, etc., this is called   output operation . Standard Input and Output in C++ is done through the use of  streams . Streams are generic places to send or receive data. In C++, I/O is done through classes and objects defined in the header file  <iostream> .  iostream  stands for standard input-output stream. This header file contains definitions to objects like  cin ,  cout , etc. /O Library Header Files There are...
Post a Comment
Read more

Genetic Algorithm: Population, Fitness Function, Parent Selection, Cross over, Mutation

Genetic Algo Population Population is a subset of solutions in the current generation. It can also be defined as a set of chromosomes. There are several things to be kept in mind when dealing with GA population − The diversity of the population should be maintained otherwise it might lead to premature convergence. The population size should not be kept very large as it can cause a GA to slow down, while a smaller population might not be enough for a good mating pool. Therefore, an optimal population size needs to be decided by trial and error. The population is usually defined as a two dimensional array of –  size population, size x, chromosome size . Population Initialization There are two primary methods to initialize a population in a GA. They are − Random Initialization  − Populate the initial population with completely random solutions. Heuristic initialization  − Populate the initial population using a known heuristic for the problem. It has been observed that the e...
Post a Comment
Read more

Difference between net platform and dot net framework...

Difference between net platform and dot net framework... .net platform supports programming languages that are .net compatible. It is the platform using which we can build and develop the applications. .net framework is the engine inside the .net platform which actually compiles and produces the executable code. .net framework contains CLR(Common Language Runtime) and FCL(Framework Class Library) using which it produces the platform independent codes. What is the .NET Framework? The Microsoft .NET Framework is a platform for building, deploying, and running Web Services and applications. It provides a highly productive, standards-based, multi-language environment for integrating existing investments with next-generation applications and services as well as the agility to solve the challenges of deployment and operation of Internet-scale applications. The .NET Framework consists of three main parts: the common language runtime, a hierarchical set of unified class librari...
3 comments
Read more