Obtaining optimal and approximate solutions to the problem of scheduling inbound and outbound trucks in cross docking operations
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Notice bibliographique
Résumé
The thesis focuses on optimization of inbound and outbound truck scheduling with the\ngoal of minimizing total operation time of cross docking. A model of cross docking is\ndeveloped; two different methods are applied on the model in order to find an optimal\ndocking sequence for receiving and shipping trucks and their assignment to receiving and\nshipping docks, and product routing from receiving to shipping trucks.\nThe two methods used were mathematical modeling and heuristic algorithm. For the first\nmethod, a mixed integer programming model was developed to minimize total operation\ntime; AMPL modeling language is used for the mathematical modeling for small sized\nproblems. For the second method, a heuristic algorithm was developed to find near\noptimal solutions fast and was used for problems of larger size. In order to examine the\nperformance of heuristic algorithm, small problems were solved by both mathematical\nmodel and the heuristic algorithm.\nThe results from the mathematical model and the heuristic algorithm are very close with\nslight differences in receiving and shipping truck docking sequence, and in product\nrouting between these two methods. In addition, the heuristic algorithm also calculates\nnumber of products transferring from receiving trucks to the temporary storage as well as\nthe number of products transferring from the temporary storage to shipping truck in\ncontrary to the mathematical model. Total number of units of products passing through\nthe temporary storage calculated by heuristic algorithm is presented and it can be seen\nthat the heuristic algorithm transfers to the temporary storage as few products as possible.\nFurthermore, in cases that receiving and shipping trucks are divided into groups or\nclusters in the cross docking operation, heuristic algorithm can be used to calculate\noptimal number of receiving and shipping docks based on preferences of total operation\ntime or total number of products passing through the temporary storage.\nAnother issue which is focused on is the problem of dock door assignment. Close\nshipping docks to each receiving dock are determined and the percentage of products\ntransferred from a receiving dock to its close shipping docks is calculated as a method to\nmeasure the performance of the dock assignment solution.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle