Developing a sustainable intermodal transportation system to enhance the efficiency of port's activities
Notice bibliographique
Résumé
Transporting millions of containers through the container terminal at the seaport per year while ensuring minimum handling operations cost and emission is challenging for the container terminals. Today, the intermodal container terminal is considered as a hearth for most intermodal transportation systems. The intermodal container terminal in the seaport is a complex system that requires careful planning in order to perform operations efficiently. Thus, inefficiently operating the terminal can slow down the flow of containers to their destination as well as increase the dwell time of the ship in the port, which leads to an increase in the total cost and affects sustainability. Consequently, there is a need for new methodologies and technologies that guarantee enhancements of terminal performance, increase capacity, and mitigate negative impacts on the environment. In a large number of cases, the seaports are usually surrounded by big cities. Hence, improving new layouts for the container terminal will lead to the faster, cheaper, and more efficient transfer of containers from their origin to the destination in a sustainable way. In this study, the Port of Montreal is used as a case study to validate the proposed layout and experiments. \n \nIn my first article, titled "Developing the Seaport Container Terminal Layout to Enhance Efficiency of the Intermodal Transportation System and Port Operations - Case of the Port of Montreal," we developed a new container terminal layout. An efficient layout of the container terminal can be achieved by reducing the distance and disposition between the quay and rail tracks. We propose a novel layout to reduce the cost and accelerate container flow, thus improving the handling system's effectiveness. We develop a MILP model to estimate and analyze the performance considering the arcs congestion for the current layouts and the new proposed layout. We present a study case on The Port of Montreal to validate the suggested solution. We found that the projected layout reduces the total cost and time for transporting containers from the port to their destination. \n \nDespite the advantages of intermodal transportation, it still has undesirable effects connected with congestion and emission. In the second article, titled "Optimization of Container Terminal Layouts in the Seaport - Case of Port of Montreal," the intermodal transportation system and its effect on port efficiency were addressed. The article investigates the role of the proposed layout in minimizing the cost of transport containers from the ship to the final destination and emissions generated from these operations. The proposed layout can improve the sustainability of port activities by decreasing the distance between the berth and interface points as well as avoiding double handling. The model was formulated as multi-objective optimization, and we use the ε-constraint method to solve the problem. The results illustrate that the proposed layout resulted in a considerable reduction in both the total cost of transport containers to their final destination and emission associated with these operations. \n \nSince different modes of transportation and resources interact and function together, the system is becoming quite complex to understand its behaviour and predict the effect of changing in some parameters. In this regard, we developed a simulation model in the third paper titled "A Simulation Approach to Compare Different Container Terminal Layouts." A discrete simulation model is developed using the SIMAN simulation language and then implemented through the Arena software application. This study aims to improve the performance and handling capacity of the terminal by recommending a new layout. Computational experiments were conducted to evaluate and compare both layouts' performance using data collected from the Port of Montreal. The results indicate that terminal layout design has a significant impact on terminal performance under the configuration of different transportation modes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».