Environmental Assessment of Shipment Release Policies
Bibliographic record
Abstract
Purpose - A program of shipment consolidation (SCL) is the purposeful intervention by management to regularly combine several small shipments so that a larger load may be dispatched on the same vehicle. SCL decisions traditionally have been based upon minimization of total logistics costs (inventory plus transportation). The paper aims to answer the following research question: given the environmental implications of vehicle emissions as a function of load weight, are the familiar SCL policies still optimal?Design/methodology/approach - Nonlinear expressions relating carbon dioxide (CO2) emissions to vehicle weight, and parameterized by trip length and average travel speed, were derived from published experimental data. Those expressions were included in a simulation model that assessed the environmental impact, in addition to the logistics cost, of the policies concerning when to release a consolidated load.Findings - For short holding times, the quantity policy performs best in terms of both logistics cost and pollution reduction. In the case of low-order arrival rates and long holding times, the time policy is best at reducing emissions and logistics costs. However, the best dispatch policy conflicts in terms of pollution reduction and logistics cost minimization for the following cases: moderate holding times and long holding times combined with high-order arrival rates. In these cases, it is necessary to consider the speed of travel, trip length and unit cost of emissions when evaluating the policies.Research limitations/implications - A carbon trading market appears to be on the horizon in several industries, which will establish a price per unit weight for CO2 emissions and make it beneficial to minimize the total cost (including emissions) of the network. This research only considers CO2 pollution, but future investigations could also consider other pollutants such as nitrogen oxides, carbon monoxide and volatile organic carbons.Practical implications - SCL policies can include a “green logistics” component that is based on empirical data. Originality/value - One undesirable consequence of transportation by truck is CO2 emissions. However, the impact can be lessened, while still emphasizing total logistics cost per load, with our simulation-based results for shipment release policies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".