In pharmaceutical R&D, decision makers face a large portion of uncertainty in portfolio decisions. Existing optimization tools are mostly based on expected values, ignoring uncertainty, and most often deliver a single, "best" selection of projects. A decision tree approach can aid decision...

Analyses in the past decade and more recently, catastrophic events, including extreme temperatures, unpredictable weather patterns, floods, and wildfires caused by climate change, have become too common worldwide. There is overwhelming evidence that country commitments expressed in National...

This study proposes a logical Petri net model to leverage the modeling advantages of Petri nets in handling batch processing and uncertainty in value passing and to integrate relevant game elements from multi-agent game processes for modeling multi-agent decision problems and resolving...

The Intuitionistic Fuzzy Set (IFS) is a powerful extension of Fuzzy Set (FS) used to handle vagueness and uncertainty. The correlation coefficient is an established tool for finding the strength of relationships between two IFSs. This study proposes a new approach for finding a correlation...

Entropy plays a vital role within fuzzy set theory as it quantifies the level of uncertainty present in the data. This study proposes a novel entropy measure tailored for Picture Fuzzy Sets (PIFS). This entropy measure is formulated based on the axioms developed for PIFS entropy, ensuring its...

The Muirhead mean (MM) operator is effective and feasible and is used for aggregating the finite collection of attributes into a singleton set, where the averaging and geometric aggregation operators are the special cases of the MM operator. Furthermore, the Complex Single-Valued Neutrosophic...

Pythagorean fuzzy sets and Fermatean fuzzy sets are used to enhance the flexibility of intuitionistic fuzzy sets for decision-making under uncertainty in fuzzy environments. This study presents and compares a new definition of quartic fuzzy sets with intuitionistic, Pythagorean, and Fermatean...

With the extensive applicability of machine learning classification algorithms to a wide spectrum of domains, feature selection (FS) becomes a relevant data preprocessing technique due to the high dimensionality of data used in these domains. While efforts have been made to study various filters...

Evaluating maintenance plans for power generation is a critical task managed by the National System Operator, as it is directly related to criteria such as operational cost, rationing, and availability of natural resources. This study identifies the most suitable maintenance schedule between...

Understanding in which contexts professionals come to trust their gut is critical both for human relations as well as for human-computer interaction. A prominent viewpoint promotes a deliberate trust development approach for professionals in all industries and at all levels of organizations...