The process of containerization and its continuous development involves changes and technological innovations in containerships and maritime container terminals. In the current era of "gigantism", despite existing fleet overcapacity, shipping companies are booking larger and fuel-efficient vessels to benefit from economies of scale and to reduce operating costs. Consequently, port terminals have to cope with unprecedented container volumes and increasing demands, as a result, handling operations are likely to be subject to delay.
In this context, container terminals are dealing with the huge challenge of readjusting themselves in order to, on one hand, improve productivity and level of service offered to the customers (minimize turnaround time) and, on the other hand, to manage terminal handling operations efficiently with the aim of reducing operating costs and becoming more competitive.
Moreover, considering that adapting facilities and terminal infrastructures involves large investment and given the lack of space in many urban ports for expanding the operational area, the improvement of handling operations efficiency is more important than ever. Thus, many efforts are required to improve the productivity of container terminals by introducing efficient solutions and optimization techniques to decision-making processes and, on the other side, introducing technological improvements such as the automation of handling equipment.
In light of this, this thesis is focused on the optimization of handling operations in the storage yard, which is considered to be the most complex terminal subsystem since terminal performance depends on its efficiency.
In particular, it attempts to: (1) determine optimal storage space utilization by considering the yard inventory and congestion effects on terminal performance; (2) introduce new allocating storage strategies with the aim of minimizing the amount of rehandling moves, which are considered to be the most important cause of inefficiency in container yard terminals, and; (3) develop a generic storage pricing schedule to encourage customers to pick up their containers promptly and, as a consequence, reduce the average duration of stay, avoiding yard congestion.
In order to tackle these issues, two different analytical models are introduced in this thesis. The first one aims to forecast storage yard inventory by dealing explicitly with stochastic behavior, yard inventory peaks and seasonal fluctuations. The second one, which is based on probabilistic and statistical functions, is derived to estimate the average number of rehandles when containers with different departure probabilities are mixed in the same stack.
Finally, the numerical experiments presented in this thesis prove the usefulness of the different analytical models, yard design methods, cost models and operative and tactical strategies developed herein. These can be applied by other researchers, planners and terminal operators to optimize the yard handling processes, to improve their efficiency rates and to increase terminal throughput without incurring large investment. By being technically efficient, the terminal will be more cost-efficient as well, resulting in the overall optimization of terminal performance.
| Identifer | oai:union.ndltd.org:TDX_UPC/oai:www.tdx.cat:10803/277420 |
| Date | 22 July 2014 |
| Creators | Martín Alcalde, Enrique |
| Contributors | Saurí Marchán, Sergi, Universitat Politècnica de Catalunya. Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports de Barcelona |
| Publisher | Universitat Politècnica de Catalunya |
| Source Sets | Universitat Politècnica de Catalunya |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis, info:eu-repo/semantics/publishedVersion |
| Format | 172 p., application/pdf |
| Source | TDX (Tesis Doctorals en Xarxa) |
| Rights | info:eu-repo/semantics/openAccess, L'accés als continguts d'aquesta tesi queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
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