A Multistakeholder Approach to the Airport Gate Assignment Problem: Application of Fuzzy Theory for Optimal Performance Indicator Selection

Airport gate assignment performance indicator selection is a complicated decision-making problem with strong subjectivity and difficulty in measuring the importance of each indicator. A better selection of performance indicators (PIs) can greatly increase the airport overall benefit. We adopt a multicriteria decision-making approach to quantify qualitative PIs and conduct subsequent selection using the fuzzy clustering method. First, we identify 21 commonly used PIs through literature review and survey. Subsequently, the fuzzy analytic hierarchy process technique was employed to obtain the selection criteria weights based on the relative importance of significance, availability, and generalisability. Further, we aggregated the selection criteria weights and experts’ score to evaluate each PI for the clustering process. The fuzzy-possibilistic product partition c-means algorithm was applied to divide the PIs into different groups based on the three selection criteria as partitioning features. The cluster with highest weights of the centre was identified as the very high-influence cluster, and 10 PIs were identified as a result. This study revealed that the passenger-oriented objective is the most important performance criterion; however, the relevance of the airport/airline-oriented and robustness-oriented performance objectives was highlighted as well. It also offers a scientific approach to determine the objective functions for future gate assignment research. And, we believe, through slight modifications, this model can be used in other airports, other indicator selection problems, or other scenarios at the same airport to facilitate policy making and real situation practice, hence facilitate the management system for the airport.

Research on the Evaluation Model for Wireless Sensor Network Performance Based on Mixed Multiattribute Decision-Making

Many application fields initiate using wireless sensor network (WSN), and the evaluation for its performance becomes an important topic, which can help the decision-maker to find the deficiency of the current WSN or seek the best WSN. There exist mixed multiple attributes in the WSN performance evaluation process, for example, some evaluation indicators can be expressed as interval numbers, while others can be expressed as linguistic variables, so it is necessary to explore the evaluation model based on mixed multiattribute decision-making (MADM). Considering the specific evaluation purpose and requirements for different enterprises, this paper puts forward an indicator selection method and a subjective weighting method based on the rough set theory. After that, based on the transformation of mixed attributes into the unified intuitionistic fuzzy numbers (IFNs), an objective weighting method based on intuitionistic fuzzy entropy is proposed. Meanwhile, the combined weights of indicators are obtained by synthesizing the subjective and objective weights. Subsequently, in order to evaluate WSN performance objectively, an integrated comprehensive evaluation framework is proposed, which includes single evaluation, compatibility test, combination evaluation, and consistency test. The paper gives specific models and calculation steps in detail. Finally, it provides a case study to explain the application of the proposed indicator selection method and the evaluation models, which provide new ideas and references for WSN performance evaluation.

A framework to identify indicators for evaluating car sharing systems

A comprehensive evaluation indicator system is the basis of car sharing systems (CSS) evaluation. The purpose of this study is to introduce the principles and methods of indicator selection for CSS, and to identify indicators for evaluating car sharing systems due to the reason that the importance of indicators can never be overestimated in CSS evaluation. A framework to identify indicators for evaluating CSS is proposed with four steps. First of all, the structure for indicator selection is established with application of AHP method. Secondly, adequacy check and redundancy check are carried out to ensure the structure is adequate and redundant. Thirdly, underlying individual indicators are proposed according to questionnaires. Fourthly, to ensure the necessity, identification, and feasibility of indicators, we conduct N-I-F check. We carry out a case study of CSS evaluation indicators to validate the proposed framework from four dimensions: economic, environmental, systematic, and social. The proposed framework is quantitative and it is helpful in CSS evaluation to identify proper indicators and find out the best CSS option.