The hybrid mathematical model for the evaluation and selection of iron ore raw materials in the context of the European Green Deal

mathematical model for evaluating and selecting iron ore raw
materials in the context of the EU Green Deal is carried out. The
necessity of developing decision support systems within the
framework of the EU Green Deal concept is substantiated, in order to
increase the degree of validity of decision-making in the evaluation
space, regarding the green course and achieving the goals of the green
agreement. For the first time, a systematic theoretical-multiple model
of the problem of evaluation and selection of iron ore raw materials,
according to the proposed factors of chemical composition, cost, and
environmental policy of the manufacturer. The problem of multicriteria selection of alternatives based on the imaginary alternative of
the "satisfaction point" of the decision-makers (DM) requirements
using the information model of criteria for evaluating the properties
of the object of study on the chemical composition of iron ore raw
materials. For the first time, a hybrid mathematical model of multicriteria evaluation of iron ore raw materials with target needs was
developed: quality of chemical composition of iron ore raw materials;
the cost of iron ore; environmental policy and environmental impact
in the extraction and/or enrichment of iron ore raw materials. The
results of a study on a real example of evaluation and selection of
iron ore concentrate for six alternatives implemented by Metinvest
(Ukraine) were tested. The general step-by-step algorithm of the
evaluation concept is described, which can be quickly implemented
in the software product for the application. The developed model will
be a useful tool for various programs of state support/business
assistance in the procurement of iron ore raw materials by reasonably
choosing a supplier using targeted needs in the context of
synchronization with the EU Green Deal initiative. Raw material
extraction and subsequent transport logistics are especially important
for the engineering industry, the electrical engineering industry, and
the automotive industry, with strong potential for the aeronautics and
aerospace industry.