Simulation study of a two‐level warehouse inventory replenishment system
Bibliographic record
Abstract
Purpose This paper aims to discuss a simulation study for a multi‐product, two‐echelon inventory replenishment system. The paper compares a one‐warehouse N‐retailer replenishment system to a two‐warehouse, N‐retailer system with cost per unit of distribution and delivery lead‐times as the performance measures. The purpose is to demonstrate that under specific circumstances a two warehouse N‐retailer inventory replenishment system provides better customer service without significant changes in the cost. Design/methodology/approach Mathematical modeling and simulation methodology is used to test the performance of the proposed two warehouse N‐retailer system and statistical analysis is used to compare the performance of several scenarios. Findings The two warehouse replenishment system indeed reduces delivery lead‐times, used as a measure of customer service, under specific conditions such as controllable freight costs. Research limitations/implications Caution should be exercised when interpreting these findings as the historical data used was from a single source. The paper did not investigate the effects of variable shipping costs from the manufacturing plant, warehouse and retailer. Future research could also consider multiple second level warehouses. Practical implications The findings provide a persuasive argument for manufacturers struggling with performance issues and channel relationships. Moreover, in addition to contributing to efficiency of distribution, two level systems can also enhance ability to adapt to local market conditions and to unexpected demand variations. Originality/value The model examined in this paper addressed a specific case for one company. While freight costs and warehousing costs will vary across companies, the cost represented here may be used as a gauge for evaluating systems with cost structures in the vicinity of those for the company represented in this paper. Additionally, the model is amenable to substitution of other firms' cost structures.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".