Machining operation optimization improves the quality of the product, reduces cost, enhances overall efficiency by reducing human error, and enables consistent and efficient operation. It is a vital decision-making process and achieves the best solution within constraints. It reduces reliance on machine-tool technicians and handbooks to identify cutting parameters, as a lack of awareness of the optimal combination of machining parameters leads to several machining inefficiencies. Subsequently, the optimization of the machining process is more useful for units of production, particularly machining units. In multi-objective optimization (MOO) problems, weights of importance are assigned, mostly identical. But, nowadays, the weights assignment techniques have received a lot of consideration from the professionals and researchers in MOO problems. Various techniques are developed to assign weights of significance to responses in MOO. The Entropy weights method (EWM) continues to work pleasingly across diverse machining operations to allocate objective weights. In this paper, a literature review is conducted to classify the articles on EWM applications in machining operations. The categorization proposal for the EWM reviews included 65 academic articles from different journals, books, and conferences since the year 2009. The EWM applications were separated into 18 categories of conventional and non-conventional machining operations. The implementation procedure of EWM is presented with an example along with method development. Scholarly articles in the EWM applications are further inferred based on (1) implementation of EWM in different machining operations, (2) MOO methods used with entropy weights in machining operations, (3) application of entropy weights by citation index and publication year, and (4) entropy weights applications in other fields. The review paper provided constructive insight into the EWM applications and ended with suggestions for further research in machining and different areas.

Revealing the benefits of entropy weights method for multi-objective optimization in machining operations: A critical review

Associate Editor of the Journal of Computer and System Sciences

In real world, a typical decision-making problem in the medical field can be seen as an uncertain hesitant fuzzy multiattribute decision-making problem when existing experiences of decision-makers are insufficient. A three-way decision model is an effective tool to deal with uncertain decision-making problems, which can realize the classification of objects. However, different psychological behaviors of decision-makers are likely to affect decision-making results in actual decision-making processes. In order to address this challenge, we first propose a regret-theory-based three-way decision model in hesitant fuzzy environments, which mainly combines regret theory with hesitant fuzzy sets to calculate the perceived utility value of objects. Second, since one of the core ingredients for regret theory is the regret–rejoice function, we put forward a new regret–rejoice function that preserves the original indecisive uncertainty in hesitant fuzzy environments. In addition, according to the inherent relationship of the used data, this article provides a three-way classification method based on the preference ranking organization method for enrichment evaluations I method. Finally, the practicability, rationality, and superiority of the proposed method are shown via the case analysis and comparative analysis in the medical field. 

Regret Theory-Based Three-Way Decision Model in Hesitant Fuzzy Environments and Its Application to Medical Decision

A hybrid decision making approach for new service development process of renewable energy investment

The present study introduces a decision-making approach with the combined compromise solution (CoCoSo) under intuitionistic fuzzy sets (IFSs) named as the IF-CoCoSo method based on proposed divergence measures and score function. The aim of the presented approach is to obtain an effective solution for multi-criteria decision-making problems on IFSs context. In this line, a new procedure is presented to derive the criteria weights using generalized score function and parametric divergence measures of IFSs. To compute the criteria weight, a generalized score function and parametric divergence measures are developed on IFSs and discussed some interesting properties. Further, the presented approach is applied to rank and evaluate the therapies for medical decision making problems, which demonstrates its applicability and feasibility. Finally, comparative and sensitivity analyses are discussed for validating the developed method.

/pdf/new-intuitionistic-fuzzy-parametric-divergence-measures-and-1o9ta2j4.pdf

New intuitionistic fuzzy parametric divergence measures and score function-based CoCoSo method for decision-making problems

Entropy is a significant mathematical instrument for determining ambiguous/fuzzy information. Entropy is indispensable for measuring ambiguity, first familiarized by Shannon (Syst Tech J 27:379–423, 1948) to extent the degree of uncertainty in likelihood distributions. Complex info processes are extensively pragmatic in decision-making processes. Created as per the notion of an exponential exponent for the fuzzy set, our exertion offers a measure of the power of an intuitive set of exponents. This article identifies a new measure of the exponential theorem on an intuitive set of equations. In addition, the necessary properties are displayed. By analyzing the results of the examples, it has been shown that this method is faster and more effective in practice.

A new parametric generalized exponential entropy measure on intuitionistic vague sets

The expansion of the online food delivery apps (OFDAs) around the globe has accelerated because of the sudden growing cases of the COVID-19 pandemic. OFDAs are quickly expanding in India, providing a huge number of chances for different OFDA platforms and creating a competitive market. There are several criteria and dimensions for OFDAs businesses to explore to keep with the frequently changing competitive market and achieve long-term success. A Pythagorean fuzzy set (PFS) is a powerful tool for dealing with uncertainty. Distance measure of PFS is a hot research topic and has real-life applications in many areas, such as decision making, medical diagnosis, patterns analysis, clustering, etc. The article aims to examine the results of the novel Pythagorean fuzzy distance measure strategy to select the best online app using TOPSIS method to select the best OFDAs. Firstly, all the axioms related to distance measures are proved for the proposed measures. The proposed work uses five distinct alternatives/options and four attributes/criteria in a fuzzy environment to deal with imprecise and conflicting information. The findings indicate that the proposed methodology is a more realistic way to choose the best OFDAs among others. Finally, a sensitivity analysis is used to determine whether the chosen alternative was the best option among the other components and to ensure that the TOPSIS technique results were accurate.

Distance Measures of Pythagorean Fuzzy TOPSIS Approach for Online Food Delivery Apps

Information theory was introduced by Shannon in 1948 and it includes the study of uncertainty measures. Analogous to information theory which is based on probability theory fuzzy set theory was developed by Zadeh in 1965 which is a mechanism to manage uncertainty. The pedestal for present study is information theory and fuzzy set theory which is termed as fuzzy information theory. In this paper a new fuzzy entropy measure is proposed for two fuzzy sets A which is based upon fuzzy entropy given by Pal and Pal [7] with some of its properties.

On some generalised exponential entropy for fuzzy sets

A new definition for quartic fuzzy sets with hesitation grade applied to multi-criteria decision-making problems under uncertainty

In our daily life, we always choose to access our decisions so that we can gain greatly from them based on our prior experiences. However, it might be challenging to reach the best decision in a fair amount of time due to the complex environment and lack of information about the system due to human error these days. Triangular fuzzy numbers are proving to be quite useful in many application fields because of their apparent flexibility in coping with the imprecision or uncertainty in the process of multi criteria decision making. A technique for order preference by similarity to ideal solution presents a solution for decision-makers that are usually multi attributes and involves a complex decision-making process. It is utilized due to its ability for considering both the qualitative and quantitative measures. The goal of this paper is to employ a technique for order preference by similarity to ideal solution‐based methodology to solve multicriteria group decision‐making problems proposed for triangular fuzzy environment. Proofs of axiomatic properties for distance measures is also discussed. Sensitivity analysis is used to improve the efficacy of the proposed measures. Comparison with the present measures is also performed. Our method requires fewer calculations and produces the improved results faster than previous methods. 

https://link.springer.com/content/pdf/10.1007/s12597-023-00627-2.pdf

Some distance measures for triangular fuzzy numbers under technique for order of preference by similarity to ideal solution environment

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