An indirect preference-based approach to estimate missing information in unconventional emergency decision-making.
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| Title: | An indirect preference-based approach to estimate missing information in unconventional emergency decision-making. |
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| Authors: | Xia, Xuan1 (AUTHOR), Gong, Zaiwu1 (AUTHOR) zwgong26@163.com, Zhou, Kun1 (AUTHOR), Wei, Guo2 (AUTHOR) |
| Source: | International Journal of General Systems. May2026, Vol. 55 Issue 4, p436-471. 36p. |
| Subjects: | Integer programming, Emergency management, Regression analysis, Stated preference methods, Conflict management |
| Abstract: | Time constraints and cognitive limits in unconventional emergencies hinder experts from offering complete preferences relations. By utilizing linear uncertain distributions to characterize the preferences of experts, a novel method for predicting missing values in linear uncertain preference relations is proposed. Current methods typically complete preference relations using direct preference information. However, the limited objective information lowers consistency and decision reliability. Therefore, it is crucial to mine additional subjective indirect preference information. In this paper, the ordinal regression model and the conflict elimination 0–1 integer programming model are constructed by integrating both subjective and objective information. The prediction results can reflect experts' implicit views. Besides, Conflicts arising from the roughness of indirect preference information are resolved, ensuring additive consistency and more accurate outcomes. To demonstrate the effectiveness of our proposed approach, a case study involving a flood event and a comparative analysis with previous methods are presented. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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