博士 / 國立交通大學 / 交通運輸研究所 / 91 / Liner shipping is a capital-intensive industry. Provision of liner shipping services, often offering global or regional coverage, requires extensive infrastructure in terms of container ships, equipment (e.g. containers, chassis, trailers), terminals and assigns agencies. With the current fiercely competitive market, freight rates cannot be increased easily, and it is costly to reposition empty containers due to trade imbalances. As a result, liner companies have difficulty generating reasonable profits and even run deficits. Therefore, liner carriers require dramatic changes in operational practices to face this tough and fluctuating market. Revenue management (RM), alternatively known as yield management (YM), can be defined as the integrated management of price and inventory to maximize a company’s profitability. RM has been enabling airlines to sell the right service to the right customer, at the right time for the right price, and thus achieves the highest amount of revenue possible. Proven to be an effective tool in the airline industry, RM has considerable potential for the liner shipping industry.
To provide carriers with a good solution to build RM systems, the RM concept is introduced to the industry to create a liner shipping revenue management (LSRM) model, which consists of two major components: (1) long-term planning, which can assist with longer term customer management, cost management, market monitoring, service route planning and ship scheduling; and (2) short-term operations, which can assist with voyage revenue optimization in terms of demand forecasting, slot allocation, pricing, container inventory control and dynamic space control. Additionally, such a system should be integrated with freight revenue, cost, container inventory database and accounting systems.
In the proposed LSRM system, service route planning and ship scheduling are aimed to provide decision support to plan new service routes and modify or integrate current service network so that companies can maximize the shipment potential. Since a service route of a containership fleet, once determined, is hard to alter for a certain period of time, the initial ship scheduling decision and cost analysis should be made carefully after comprehensive studies and planning. Liner shipping companies can benefit greatly from using systematic methods to improve ship scheduling and cost analysis on service route planning. This study proposes a dynamic programming (DP) model for ship scheduling and clarifies cost items for planning a service route. This can help planners make better scheduling decisions under berth time-window constraints, as well as to estimate voyage fixed costs and freight variable costs more accurately. The proposed DP ship scheduling model derives an optimal scheduling strategy including cruising speed and quay crane dispatching decisions, rather than a tentative and rough schedule arrangement. Additionally, the model can be extended to cases of integrating one company’s or strategic alliance partners’ service networks to gain more efficient hub-and-spoke operations, tighter transshipment and better level-of-service. This improvement not only gives this new mathematical model, but also could yield cost savings due to decreases of vessel fuel consumption and port time.
Containership capacity is a vitally important consideration since there is no revenue derived from unused space. Thus, containership capacity allocation is an important issue since carriers must avoid unused space on a voyage in order to derive the highest possible revenue from containership capacity. In the face of uncertain cargo demand and fiercely competitive markets, liner carriers should refine their business activities to maximize voyage profits through careful consideration of slot allocation and pricing. In this study, some relevant containership slot allocation models are formulated and implemented through mathematical programming and fuzzy multi-objective programming. The objective of the proposed slot allocation model (SA1) is to maximize the total freight contribution instead of freight revenue, due to high variable costs in the liner shipping. We considering the possibility of a continuous worsening situation of trade imbalances, so trade imbalance factors and repositioning costs are included in the objective function. The other one (SA2) of the models is proposed to deal with two conflicting objectives: carrier’s freight contribution and agents’degree of satisfaction, as well as fuzzy constraints, i.e. uncertainties of cargo transportation demand and weight. Interactive fuzzy multi-objective linear programming with fuzzy parameters is applied to solve this problem. We illustrate this slot allocation model with a case study of a Taiwan liner shipping company to test its efficacy. Results show the model’s applicability and excellent performance in practice.
| Identifer | oai:union.ndltd.org:TW/091NCTU0118038 |
| Date | January 2003 |
| Creators | Shih-Chan Ting, 丁士展 |
| Contributors | Gwo-Hshiung Tzeng, 曾國雄 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | en_US |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 136 |
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