The use of MCDMs, or Multi-Criteria Decision Making Methods, in various aspects of research has increased dramatically in recent years. The total number of papers on MCDMs is 1298 in 2022, compared to only 51 in 1999. That translates to a 25.45-fold increase in the number of research papers published in journals of Elsevier Publishers.
If we categorize the papers based on the objective of MCDM application, we can broadly divide the published papers into the seven perspectives listed below. MCDMs are used for other purposes as well, but the number of papers on those topics is limited.
Location/Site Selection
MCDMs are frequently used to identify an ideal site or location for the installation or relocation of some industrial units, power plants, business centers, market complexes, and so on. The main objective of MCDM applications remains to consider some factors and identify the best location among the multiple locations available for selection.(Example : Nagababbu et.al.,Bairagi, B)
Performance Evaluation
MCDM techniques were used in several papers to analyze the performance of a product, an industry, or a proposed project. In a few cases, the application of some techniques was used to evaluate some models/formulae/applications.(Example: Nkuna et.al., Stevic et.al.)
Benchmark Development
The creation of benchmarks is critical in performance analysis. The goal included developing benchmarks for evaluation using MCDM techniques, and then applying the technique to evaluate the performance of some products/processes/etc. by comparing the performance to the developed benchmark. (Example: Lohakare et.al., Sumrit et.al.)
Development of Decision Support Systems
MCDMs are also used in the development of integrated decision support systems. This technique is primarily used for the development of the DSS's logic, which is used by the system to make decisions. DSS are used to achieve a variety of goals such as supplier selection, material selection, disaster management, and preventive measurements. (Ghazi et.al., Namin et.al.)
Vulnerability/Risk Analysis
Another objective where MCDMs are used alternatively is vulnerability/risk analysis. Vulnerability is the process of identifying and analyzing potential issues that could negatively impact the system's key objectives. Risk is the process of identifying and analyzing potential issues that could negatively impact the system's key objectives. Both vulnerability and risk involve a lot of decision-making through prioritization, comparing with benchmarks, or feature selection. MCDM is a technique for decision-making objectives such as prioritization, feature selection, and so on. That is the reason why there is a large number of papers on the application of MCDMs in vulnerability or risk analysis. (Mondal et.al., Tanim et.al.)
Index Development
An index is a metric or indicator about something. In the stock exchange, an index is used to measure the performance of any particular aspect of the market. The index developed for ecological studies is used to quantify and summarise ecological conditions at multiple levels. The weights of significance assigned to the input parameters based on their impact on the output are used to create an index. The primary goals of all compensatory MCDMs(Compensatory and Outranking techniques comprise the two categories of MCDMs. The distinction between the two is explained in my MCDM lecture notes.) (such as AHP, ANP, MACBETH, and so on) are to determine the weights of the input parameters so that the output can be used as a single point or number indicator of the inputs. As a result, MCDMs are widely used in the development of indicators. (Example: Gavalas et.al., Pathan et.al.)
Prioritization
The process of determining the level of importance and urgency of a task, system, event, etc. is known as prioritization. Prioritization is broadly equivalent to a process for identifying the best solution among many available solutions. The MCDM techniques were discovered to be ideal for use in prioritizing a list of solutions or options in order to identify the most optimal among them. (Example: Sarkar et.al., Ghasemlouniaa and Utlub)
Examining the published papers revealed that many times, multiple MCDMs were used in a hybrid mode by researchers rather than just one. GIS is sometimes used to visualize the technique's output. The most commonly used technique under MCDM is AHP, which is followed by Fuzzy Logic. Even in situations where there is a high degree of certainty, different MCDMs can produce inconsistent rankings of the alternatives. When two different MCDM techniques are used on the same decision problem, they can produce two different solutions. Because of this, the two most difficult tasks for a new researcher when developing an MCDM-based methodology are the selection of an appropriate analytic method and the interpretation of the MCDM results.
Thank you for reading the article. If you have any comments kindly hit them to me.
No comments:
Post a Comment