港口公用碼頭船席指派最佳化之研究;Optimization of Berth Allocation to Public Wharfs in a Harbor

NCUIR > Engineering College > Department of Civil Engineering > Research Project > Item 987654321/61936

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/61936

Title:	港口公用碼頭船席指派最佳化之研究;Optimization of Berth Allocation to Public Wharfs in a Harbor
Authors:	顏上堯
Contributors:	國立中央大學土木工程學系
Keywords:	土木水利工程
Date:	2014-03-11
Issue Date:	2014-03-11 12:29:03 (UTC+8)
Publisher:	行政院國家科學委員會
Abstract:	研究期間：10308~10407;The effective allocation of berths is an important issue for harbor bureaus, requiring consideration of operating objectives and constraints related to the berths and the ships. Currently, such allocations are made manually based on staff experience, which is not only inefficient, but also difficult to ensure solution quality, often resulting in inferior solutions. Moreover, in actual operations, stochastic ship arrivals (early or late arrivals) can often occur to disturb the original plan. Furthermore, recently, the trend has been for major oceanic carriers to enter into alliances with other carriers as a means of attaining a more efficient level of operations and reducing their operating costs. However, currently, in Taiwan and other countries, most berth allocation is still done on a trial-and-error process. This manual approach, without optimization from a systemic perspective, may not only reduce the effectiveness of the strategic alliance, but also the berth allocation efficiency in the harbor. Therefore, in this research, based on the system optimization perspective, we will develop a basic berth allocation model based on the general berth assignment rules, a stochastic berth allocation model that incorporates stochastic ship arrival times, several berth allocation models for strategic alliances, and solution algorithms capable of efficiently solving these models. These models are expected to be useful tools for helping the planner to effectively and efficiently solve such berth allocation problems. A preliminary evaluation indicates that this study can be expected to be complicated and its scope is large, so we propose a three-year project. In the first year, we will construct a basic berth allocation model (Deterministic Model, DM) based on the general berth assignment rules of public wharfs in a harbor, given deterministic ship arrival times. In the second year, extending the DM established in the first year we will construct a stochastic berth allocation model (Stochastic Model, SM) that incorporates stochastic ship arrival times. In the third year, we will construct two berth allocation models for strategic alliances (ADM and ASM), based on the DM and the SM developed in the first and second years. We will employ network flow techniques to develop all the models, each including deterministic/stochastic berth allocation network, with or without considering strategic alliances, to formulate the flows of berths in the dimensions of space and time. Suitable side constraints will be set in the DM, SM, ADM and ASM to comply with real operating requirements. All the models are expected to be formulated as special integer multiple commodity network flow problems, which are characterized as NP-hard and cannot be optimally solved in a reasonable time for realistically large problems. In order to efficiently solve large-scale problems such as occur in the real world, we will develop a solution algorithm for each model, based on Lagrangian relaxation with subgradient methods. Finally, to test how well the models and solution algorithms can be applied in practice, case studies will be performed using real data from a domestic seaport operation. Computerized random generators will also be designed to generate different problem instances which will be used for testing the models and solution algorithms. Finally, conclusions and suggestions will be given.
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Department of Civil Engineering] Research Project

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	351	View/Open

社群 sharing

Loading...