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Evaluations of grey systems and systems with subjective judgements are always like an impasse for science and companies. Especially, calculations of the problems which include various units are really difficult situations. The purpose of this paper is to propose a grey analytic hierarchy process (G-AHP) for engineering and managerial problems with grey systems to make more clear and objective decisions.

Proposed G-AHP approach is applied to project manager selection for a software project of an energy company. The application includes three different units as year, score and assessment. Six engineers are evaluated with 25 criteria in the application. Weights of the factors and assessments are done by three top managers of the company as pairwise comparisons. Other data in the decision matrix are obtained from the personal information and exam results of engineers.

Final weights of the criteria and evaluations of engineers are all done with the proposed G-AHP. Obtained results of G-AHP are also compared with grey “VlseKriterijumska Optimizacija I Kompromisno Resenje” results as a validation of the calculations and proposed approach. Final results of the applications are ranked for the evaluations and comparison. All results of the case study are concluded with the effectiveness and applicability of the proposed G-AHP method both for this study and other fields of science, engineering and management.

This study provides to evaluate and interpret grey systems with different units and subjective judgements for science, engineering and management more clearly and objectively in an easier way.

This paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.

The drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.

The findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.

The HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.

The validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.

During the service period of communication satellite systems, their performance is often degraded due to the depletion mechanism. In this paper, the grey system theory is applied to the multi-state system effectiveness evaluation and the grey Lz-transformation ADC (availability, dependability and capability) effectiveness evaluation model is constructed to address the characteristics of the communication satellite system such as different constituent subsystems, numerous states and the inaccuracy and insufficiency of data.

The model is based on the ADC effectiveness evaluation method, combined with the Lz transformation and uses the definite weighted function of the three-parameter interval grey number as a bridge to incorporate the possibility of system performance being greater than the task demand into the effectiveness solution algorithm. At the same time, using MATLAB (Matrix laboratory) to solve each state probability, the same performance level in the Lz transform is combined. Then, the system effectiveness is obtained by Python.

The results show that the G-Lz-ADC model constructed in this paper can accurately evaluate the effectiveness of static/dynamic systems and certain/uncertain system and also has better applicability in evaluating the effectiveness of the multi-state complex system.

The G-Lz-ADC effectiveness evaluation model constructed in this paper can effectively reduce the complexity of traditional effectiveness evaluation models by combining the same performance levels in the Lz-transform and solving the effectiveness of the system with the help of computer programming, providing a new method for the effectiveness evaluation of the complex MSS. At the same time, the weaknesses of the system can be identified, providing a theoretical basis for improving the system’s effectiveness.

The possibility solution method based on the definite weighted function comparing the two three-parameter interval grey numbers is constructed, which compensates for the traditional calculation of the probability based on numerical values and subjective preferences of decision-makers. Meanwhile, the effectiveness evaluation model integrates the basic theories of three-parameter interval grey number and its definite weighted function, Grey−Markov, grey universal generating function (GUGF), grey multi-state system (GMSS), etc., which is an innovative method to solve the effectiveness of a multi-state instantaneous communication satellite system.

The purpose of the study is to provide insights into the process of decision making. Indian Railways as an organization has to use the available resources based on thorough analysis and proper application of available evaluation methodologies.

This study uses an integrated group discussion – analytical hierarchy process (AHP) to prioritize capital-intensive Indian Railways projects.

Through an email-based survey, six important criteria for ranking upcoming domestic freight corridors were selected, and weights for these criteria were calculated through AHP. The sensitivity analysis of the decision model suggests that the results of this study are significant, reliable and robust.

This study lays a foundation for the decision-makers of Indian Railways to consider a scientific approach while finalizing the big investment projects. This paper provides essential insights on prioritizing capital-intensive transport projects and is readily applicable to any case study.