A Novel Opportunity Losses-Based Polar Coordinate Distance (OPLO-POCOD) Approach to Multiple Criteria Decision-Making

Author:

Sheikh Reza1ORCID,Senfi Soheila2ORCID

Affiliation:

1. Production and Operation Management (POM), Shahrood University of Technology, Shahrood, Iran

2. Master of Business Administration (MBA), Shahrood University of Technology, Shahrood, Iran

Abstract

The ability to make decisions is crucial for achieving success in any field, particularly in areas that involve managing extensive information and knowledge. The process of decision-making in real-world scenarios often involves considering numerous factors and aspects. It can be challenging to make decisions in such complex environments. In this paper, we present a new technique that solves multicriteria decision-making (MCDM) problems by considering opportunity losses-based polar coordinate distance (OPLO-POCOD). MCDM is a subdiscipline of operations research in which some alternatives are evaluated concerning some criteria to choose the most optimal alternative(s). Opportunity loss is a fundamental concept in economics and management, which can be used as a basis for determining the value associated with information. The authors emphasize that the technique incorporates the concept of opportunity losses and uses distance vectors in polar coordinates, making it a compelling approach. By considering opportunity losses, decision-makers gain a better understanding of the trade-offs involved in selecting alternatives, enabling them to make more informed decisions. Finally, the proposed method is exhibited through the use of numerical an example to illustrate its process. Additionally, a comparative sensitivity analysis is conducted to evaluate the outcomes of OPLO-POCOD and compare them with existing MCDM methods. The OPLO-POCOD method is found to have high reliability compared to other methods, as indicated by Spearman’s correlation coefficient, which is greater than 0.9. The method shows a correlation of over 98.5% with TOPSIS, COPRAS, ARAS, and MCRAT methods, demonstrating its robustness and effectiveness. These analyses show the efficiency of the proposed method and highlight the stability of the results.

Publisher

Hindawi Limited

Reference49 articles.

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