Multi-objective Optimization on the Basis of Ratio Analysis - MOORA

 MOORA method was widely used because of computational time is fast as well as very less number of mathematical formulations are used.

 

Introduction to MOORA 

 

Brauers introduced MOORA in the year 2004 as an objective method. In this method, the Desirable and Undesirable criteria are used simultaneously for ranking, and hence it is a Compensatory method.

This method primarily employed for Quantitative attributes only. Moora method majorly consists of two components. One is Ratio System which introduced in 2004. Later on, Brauers and Zavadskas introduced the Reference point approach in 2006. Here, it is all about the Ratio system, which widely used in many selection applications.

 

Steps in MOORA – Ratio System

 

Step 1 - Normalize the Decision Matrix

Based on the Selection problem, the alternatives and attributes values in the decision matrix. As X. Then the matrix needs to be normalized by using the formulae. This results in Xij* as a Normalized decision matrix.

 Step 2 - Estimation of Assessment Values

Here the Normalized data need to multiply with weight criteria for all the alternatives. For multi-objective optimization, these normalized performances are added in case of beneficial attributes and subtracted in case of non-beneficial attributes. 

Here the weight criteria can be estimated by using the AHP method or Entropy method.

Advantages of using MOORA method

• Very less number of mathematical equations are involved
• Computational time is fast
• Easily coded
  

 

Case study

Here a Case study used for the Selection of the Industrial Robot. There are seven alternatives of Industrial robots with Load capacity, Repeatability, Maximum tip speed, Memory capacity and Manipulator reach as the attributes. 

 

Video demonstration of the Case study

Download the Excel sheet demonstrated in the video

Reference:  Bhangale, P. P., Agrawal, V. P., & Saha, S. K. (2004). Attribute based specification, comparison and selection of a robot. Mechanism and Machine Theory, 39(12), 1345-1366.