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EN
Oil and gas industry processes are associated with significant expenditures and risks. Adequacy of the decisions on safety measures made during early stages of planning the facilities and processes contributes to avoiding technological incidents and corresponding losses. Formulating straightforward requirements for safety instrumented systems that are followed further during the detailed engineering design and operations is proposed, and a mathematical model for safety system design is introduced in a generalized form. The model aims to reflect the divergent perspectives of the main parties involved in oil and gas projects, and, therefore, it is formulated as a multi-objective problem. Application of black box optimization is suggested for solving real-life problem instances. A Markov model is applied to account for device failures, technological incidents, continuous restorations and periodic maintenance for a given process and safety system configuration. This research is relevant to engineering departments and contractors, who specialize in planning and designing the technological solution.
EN
Multi-criteria decision-making (MCDM) methods are associated with the ranking of alternatives based on expert judgments made using a number of criteria. In the MCDM field, the distance-based approach is one popular method for receiving a final ranking. One of the newest MCDM method, which uses the distance-based approach, is the Characteristic Objects Method (COMET). In this method, the preferences of each alternative are obtained on the basis of the distance from the nearest characteristic objects and their values. For this purpose, the domain and fuzzy numbers set for all the considered criteria are determined. The characteristic objects are obtained as the combination of the crisp values of all the fuzzy numbers. The preference values of all the characteristic object are determined based on the tournament method and the principle of indifference. Finally, the fuzzy model is constructed and is used to calculate preference values of the alternatives. In this way, a multi-criteria model is created and it is free of rank reversal phenomenon. In this approach, the matrix of expert judgment is necessary to create. For this purpose, an expert has to compare all the characteristic objects with each other. The number of necessary comparisons depends squarely to the number of objects. This study proposes the improvement of the COMET method by using the transitivity of pairwise comparisons. Three numerical examples are used to illustrate the efficiency of the proposed improvement with respect to results from the original approach. The proposed improvement reduces significantly the number of necessary comparisons to create the matrix of expert judgment.
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