SummaryThis paper presents a reliable, easy and more objective approach for ranking and determining preference in a multi-criteria decision-making problem within the shipping industry. Through the integration of the improved score function, fuzzy Shannon's entropy method and the interval-valued intuitionistic fuzzy M-TOPSIS method, for ranking and for representing the aggregated effect of positive and negative evaluations in the performance ratings of the alternatives based on interval-valued intuitionistic fuzzy set (IVIFS) data. The integration of the improved score function, fuzzy Shannon's entropy method and the intervalvalued intuitionistic fuzzy M-TOPSIS method in this paper has provided a whole new approach for solving multi-criteria decision-making problems. The improved score function which is applied to the calculation of the separation measures of each alternative from the positive and negative ideal solutions. Reflect and model the fuzziness and hesitation of the decision-maker subjective assessment, while the fuzzy Shannon's entropy method is been used for calculating the criteria weight. The proposed method has successfully been applied to rank and determined the most appropriate shipping partner for a shipping company located in Malaysia, and for a modified hypothetical example which is based on the selection of a preferred Ship as a reference for a new design. The model has been compared with existing model and we can conclude, it provides a better alternative method for ranking and for the determination of preference in a multi-criteria decision-making problem.
In this paper, we present an Intuitionistic Fuzzy Technique for Order Preference by Similarity to the Ideal Solution model which is based on a modified exponential score function for detecting early failure in a locally made Offshore Patrol Boat engine, with special regard to component interaction failure, using groups of experts' opinions to detect the root cause and the engine systems most affected by the failures in the Boat engine. The study is aimed at providing an alternative method for the traditional product development failure mode identification and analysis methods which hitherto are limited when it comes to component interaction accidents and failure analysis in the machine system. The results from the study show that although early detection of failures in engines is quite difficult due to the dependency of machine systems and components on each other, using an intuitionistic fuzzy multi-criteria decision-making method which is based on experts' opinions these faults/failure can easily be diagnosed and detected.
In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert's opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failuresare easily detected using expert's based opinions.
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