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Item type:Publication, Hybrid fuzzy MCDM and FMEA integrating with linear programming approach for the health and safety executive risks: a case study(Emerald, 2021-03-01)The of this study is to present a new failure mode and effects analysis (FMEA) approach based on fuzzy multi-criteria decision-making (MCDM) methods and multi-objective programming model for risk assessment in the planning phase of the oil and gas construction projects (OGCP) in Iran. Design/methodology/approach This research contains multiple steps. First, 19 major potential health and safety executive (HSE) risks in OGCP were classified into six categories with the Delphi method. These factors were distinguished by the review of project documentation, checklist analysis and consulting with experts. Then, using the fuzzy SWARA method, the authors calculated the weights of major HSE risks. Subsequently, FMEA and PROMETHEE approaches were used to identify the priority of main risk factors. Eventually, a binary multi-objective linear programming approach was developed to select the risk response strategies, and an augmented e-constraint method (AECM) was used. Findings Regarding the project triple well-known constraints of time, cost and quality, which organizations usually confront, the HSE risks of OGCP were identified and prioritized. Also, the appropriate risk response strategies were also suggested to the managers to be adopted regarding the situations. Originality/value The present research points at the HSE risks’ assessment integrating the fuzzy FMEA, step-wise weight assessment ratio analysis and PROMETHEE techniques with the AECM. Further to the authors’ knowledge, the quantitative assessment of the HSE risks of OGCP has not been done using the combination of the fuzzy FMEA, MCDM and AECMs. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enhancing multi-criteria decision-making with fuzzy logic: An advanced Defining Interrelationships Between Ranked II method incorporating triangular fuzzy numbers(Global Academic Excellence, 2024-03-15)In multi-criteria decision-making (MCDM), accurately quantifying qualitative data and simulating real-world scenarios remains a significant challenge, particularly in the presence of inherent imprecision and incompleteness of information. Fuzzy logic, recognized for its capacity to model uncertainty and ambiguity, emerges as a pivotal theory in decision-making processes. This study introduces an enhancement to the Defining Interrelationships Between Ranked Criteria II (DIBR II) method, employing triangular fuzzy numbers with variable confidence intervals for the determination of criteria weight coefficients-essential for assessing their significance and impact on final decisions. The enhanced method, hereafter referred to as the Fuzzy-DIBR II (F-DIBR II), is elaborated upon through a comprehensive description of its algorithmic steps, underscored by a numerical example that highlights its potential. Validation of F-DIBR II is undertaken via a comparative analysis against the traditional DIBR II approach, placing particular emphasis on its application within the Fuzzy Complex Proportional Assessment (COPRAS) framework, geared towards evaluating sustainable mobility measures. This focal point not only reaffirms the necessity of integrating fuzzy logic into the DIBR II methodology but also validates its practical applicability in addressing real-world issues. Contributions of this research extend beyond the theoretical enhancements of fuzzy theory within the MCDM landscape, offering tangible implications for the application of F-DIBR II in sustainable mobility analyses. The consistency in professional terminology throughout the study ensures clarity and coherence, aligning with the stringent standards of top-tier academic journals.