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A Partial Parallel Airport Gate Assignment Supported by a Knowledge-based System Combined with Mathematical Programming 被引量:2
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作者 Cheng Yu(Center for Transportation Studies, School of Civil and Structural EngineeringNanyang Technological University, Singapore, 2263) 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1996年第3期43-61,共19页
The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be consid... The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper. 展开更多
关键词 Airport operations Gate assignment Knowledge-based system mathematical programming.
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Fuzzy data envelopment analysis approach based on sample decision making units 被引量:11
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作者 Muren Zhanxin Ma Wei Cui 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第3期399-407,共9页
The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs ty... The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs typically have some levels of fuzziness. To analyze a decision making unit (DMU) with fuzzy input/output data, previous studies provided the fuzzy DEA model and proposed an associated evaluating approach. Nonetheless, numerous deficiencies must still be improved, including the α- cut approaches, types of fuzzy numbers, and ranking techniques. Moreover, a fuzzy sample DMU still cannot be evaluated for the Fuzzy DEA model. Therefore, this paper proposes a fuzzy DEA model based on sample decision making unit (FSDEA). Five eval- uation approaches and the related algorithm and ranking methods are provided to test the fuzzy sample DMU of the FSDEA model. A numerical experiment is used to demonstrate and compare the results with those obtained using alternative approaches. 展开更多
关键词 fuzzy mathematical programming sample decision making unit fuzzy data envelopment analysis EFFICIENCY α-cut.
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Double weight determination method for experts of complex multi-attribute large-group decision-making in interval-valued intuitionistic fuzzy environment 被引量:5
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作者 Bingsheng Liu Sijia Guo +2 位作者 Kaijing Yan Ling Li Xueqing Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第1期88-96,共9页
The systematic clustering analysis based weight determination methods are suitable for the experts of complex multi-attribute large-group decision-making (CMALGDM) in interval-valued intuitionistic fuzzy environment. ... The systematic clustering analysis based weight determination methods are suitable for the experts of complex multi-attribute large-group decision-making (CMALGDM) in interval-valued intuitionistic fuzzy environment. However, these methods mainly have two shortcomings: they do not consider the consistency of the experts in each aggregation; the aggregation weights are often determined simply by the 'majority principle', and neglect the quantity of information provided by the holistic aggregation, leading to decision biases. Hence, a double weight determination method for experts is proposed to solve these problems. As for the first shortcoming, a mathematical programming model is used to solve for the optimal expert weights within each aggregation, ensuring consistency in the overall preferences of the aggregations. As for the second shortcoming, we propose a modification of the aggregation weights based on the information entropy, which fully considers both the number of experts and the amount of information provided by the holistic aggregation. With the proposed method, the final expert weights are determined more rigorously and objectively. The feasibility of the proposed method is investigated through an illustrative example. © 1990-2011 Beijing Institute of Aerospace Information. 展开更多
关键词 Fuzzy sets mathematical programming
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