The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision‐making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision‐making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision‐making problems are applied to illustrate the feasibility and practicality of the proposed method.

The large amount of information handled by organizations has increased their dependance on information technologies, which has made information security management a complex task. This is mainly because they cover areas such as physical and environmental security, organization structure, human resources and the technologies used. Information security frameworks can minimize the complexity through the different documents that contain guidelines, standards, and requirements to establish the procedures, policies, and processes for every organization. However, the selection of an appropriate framework is by itself a critical and important task, as the framework must adapt to the characteristics of an organization. In this paper, a general vision of the newest versions of the NIST CSF, ISO/IEC 27001:2022, and MAGERIT frameworks is provided by comparing their characteristics in terms of their approaches to the identification, assessment, and treatment of risks. Furthermore, their key characteristics are analyzed and discussed, which should facilitate the consideration of any of these frameworks for the risk management of complex manufacturing organizations.

The random effects in a gamma process are introduced in terms of its scale parameter. However, the scale parameter affects both its mean and variance. Hence, the variation of the degradation rates and the within degradation increments are expected to be large. For some products, the random effects affect just the rate or just the volatility of the process. Thus, two modifications of the parameters' structure of the gamma process are proposed. One implies that the random effects affect just the volatility and the second just the rate. A Bayesian estimation approach is provided and implemented in two case studies.