An improved iterative stochastic multi-objective acceptability analysis method for robust alternative selection in new product development

Alternative selection in new product development (NPD) is a multi-criteria decision-making (MCDM) problem. It usually starts with incomplete, imprecise or even partially missing information. Currently, most existing methods in dealing with this problem cannot work well if required information is incomplete or missing. It is acknowledged that stochastic multi-objective acceptability analysis (SMAA) can be applied to address MCDM problem with incomplete preference information and uncertain criteria measurements. In SMAA, alternatives are evaluated based on SMAA measurements (acceptability index, central weight vector and confidence factor). The discriminability of SMAA for the optimum alternative heavily depends on differences of SMAA measurements among different alternatives. Usually, a large number of alternatives and high level of uncertainty are involved in alternative selection in NPD. In this situation, the differences among SMAA measurements are not obvious, and therefore SMAA cannot deal with such problem very well. To this end, this paper proposes an improved SMAA method called Iterative-SMAA (I-SMAA) for alternative selection in NPD. In the I-SMAA, an iterative multi-step decision-making process is suggested to improve differences of SMAA measurements among different alternatives, and thus assist decision makers (DMs) to positively discern from the most preferred alternative. To enhance the decision-making efficiency, sensitive criteria are acquired in each iteration by ranking sensitivity analysis. DMs are guided to provide partial preference information and give more accurate criteria measurements for sensitive criteria rather than all criteria. Eventually, to verify the proposed method, a numerical example of the existing literature is solved with the method, and the results are compared. And then, a practical example of a preparation equipment for coal samples is further employed to verify the practicability of the proposed I-SMAA.     

依托物理模型的叠后裂缝敏感地震属性优选与应用

在更关注中小尺度裂缝构造的现阶段，大尺度裂缝研究不可或缺。预测大尺度裂缝的常用方法是地震属性分析，因此寻找并选用对（不同尺度）裂缝敏感的地震属性成为关键。基于多裂缝参数地震物理模型，开展叠后属性分析，研究地震属性对裂缝参数的敏感性，然后优选敏感属性进行多属性融合。结果表明：在单一属性裂缝预测中，倾角约束分频相干属性具有明显优势，但难以识别三维空间某一方向尺度小于λ/4的裂缝带；频率衰减梯度属性对裂缝带尺度敏感，谱分解相位调谐体属性对裂缝密度敏感，振幅属性对裂缝方位和缝面倾角敏感；曲率等几何属性、相干属性和物理属性的融合不仅能突出大断裂，还能降低多解性。     

Fermatean fuzzy linguistic set and its application in multicriteria decision making

In this paper, we propose the concept of Fermatean fuzzy linguistic term sets based on linguistic term sets and Fermatean fuzzy sets. The basic operational laws, the score function, and the accuracy function of Fermatean fuzzy linguistic numbers are provided. Then we propose the Fermatean fuzzy linguistic weighted aggregation operator, the Fermatean fuzzy linguistic weighted geometric operator, and the Fermatean fuzzy linguistic distance measures. Furthermore, we extend the TOPSIS method to the proposed distance measures, and the ranking of alternatives is obtained under a Fermatean fuzzy linguistic environment. An example is provided to illustrate the feasibility and effectiveness of the proposed method, and a comparison with the existing method is also analyzed. Finally, the sensitivity analysis of the parameter in the proposed distance measure is also discussed.     

Multicriteria decision-making using Archimedean aggregation operators in Pythagorean hesitant fuzzy environment

In multicriteria decision-making (MCDM), the existing aggregation operators are mostly based on algebraic t-conorm and t-norm. But, Archimedean t-conorms and t-norms are the generalized forms of t-conorms and t-norms which include algebraic, Einstein, Hamacher, Frank, and other types of t-conorms and t-norms. From that view point, in this paper the concepts of Archimedean t-conorm and t-norm are introduced to aggregate Pythagorean hesitant fuzzy information. Some new operational laws for Pythagorean hesitant fuzzy numbers based on Archimedean t-conorm and t-norm have been proposed. Using those operational laws, Archimedean t-conorm and t-norm-based Pythagorean hesitant fuzzy weighted averaging operator and weighted geometric operator are developed. Some of their desirable properties have also been investigated. Afterwards, these operators are applied to solve MCDM problems in Pythagorean hesitant fuzzy environment. The developed Archimedean aggregation operators are also applicable in Pythagorean fuzzy contexts also. To demonstrate the validity, practicality, and effectiveness of the proposed method, a practical problem is considered, solved, and compared with other existing method.     

Matching of technological forecasting technique to a technology using fuzzy multi-attribute decision-making methods: Case study from the aerospace industry

Given the accelerating pace of technological advances and environmental changes, technology-based companies are required to predict and understand future events in their environments. However, there is a wide range of forecasting methods creating confusion on which method to use. This paper demonstrates the selection of an appropriate technique for technology forecasting in the Iran Aviation Industries Organization (IAIO). To this end, a review of the literature was first reviewed to extract the proper criteria for selecting a forecasting method. Next, the SWARA and fuzzy MUTLIMOORA methods were used to evaluate and prioritize a total of twelve forecasting methods proposed for the case study. The results suggested that the Delphi method for technology forecasting in the IAIO. Scenario writing and the relevance tree are the next proper alternatives that can be used.     

Looking out to look in: inspiration from social sciences for construction management research

In reaction to the recent call for critical debate in the field of construction management research, I argue that we should embrace the richness of adjacent fields of study in order to dynamically develop our own and face the plethora of contemporary societal challenges that exist in our industry. I introduce the concepts of other-than-rational thinking in decision-making and multiplicity in management responses as examples of inspirational sources from social sciences that would contribute to truly understanding the driving forces of construction management processes. I connect these concepts to contemporary studies in construction management and share my experiences with several positive collaborative approaches in conducting construction management research.     

A large group linguistic Z-DEMATEL approach for identifying key performance indicators in hospital performance management

In hospital management, performance measurement is of vital importance for improving healthcare service quality. The performance of a healthcare organization is often influenced by numerous indicators, and it is unrealistic to manage them all due to the restriction of resources. In addition, the performance measurement for improvement relates to the benefits of many departments, and it is necessary for large number of experts with different backgrounds to participate in the evaluation process of healthcare indicators. In response, this study develops a large group evaluation approach using linguistic Z-numbers and decision-making trial and evaluation laboratory (DEMATEL) to determine key performance indicators (KPIs) for hospital management. For this approach, the complex and uncertain interrelation evaluations among indicators are given by experts using linguistic Z-numbers. An extended DEMATEL method is proposed to determine KPIs based on the cause and effect relationships of performance indicators. Finally, a case study in a rehabilitation hospital is presented to illustrate the effectiveness and usefulness of the proposed large group linguistic Z-DEMATEL approach. The results indicate that incidents/errors, accidents/adverse events, nosocomial infection, nursing technology pass rate, and length of stay are KPIs for the given application.