Path Choice of Emergency Logistics Based on Cumulative Prospect Theory
Bibliographic record
Abstract
We study the problem of path choice for emergency logistics in this paper. Based on the uncertainty environment during the path choice from emergency logistics network and the bounded rationality of decision makers, cumulative prospect theory is introduced to study the problem of emergency logistics path choice with comprehensive consideration of path properties and risk attitude of decision makers. In addition, the decision behavior of decision maker with the attitude of risk seeking and risk aversion under limited rationality is comprehensively analyzed respectively. Based on the choice behavior, a strategy to demarcate the value of reference point value is also proposed, and an optimization model is used to obtain the combined weight based on the moment estimation. Finally, both the theory and model are verified by calculation and compared analysis in a case study. In addition, perturbation analyses of related parameter are carried out to further reveal the influence mechanism between the prospect value of each path and related parameters. The result shows that the decision-making model can make emergency logistics path choice with higher efficiency and reliability under different complex interference conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".