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題名：定期航運航線規劃與收益管理之研究
作者：丁士展
作者(外文)：Shih-Chan Ting
校院名稱：國立交通大學
系所名稱：交通運輸研究所
指導教授：曾國雄
學位類別：博士
出版日期：2003
主題關鍵詞：定期航運；收益管理；航線規劃；船隊排程；成本分析；艙位分配；動態規劃；模糊多目標規劃；liner shipping；revenue management；service route planning；ship scheduling；cost analysis；slot allocation；dynamic programming；fuzzy multi-objective programming
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定期航運業為資本密集的產業，航運公司航線服務涵蓋全球或區域內的港口。為維持定期的航線服務，必須投入相當大的資金，如貨櫃船隊、貨櫃、機具以及貨櫃碼頭等的投資，並指派代理行執行當地的業務。然而面臨競爭激烈的市場，運價不易提升，又因航線貿易量的不平衡，增加許多空櫃調度成本，更增加了運價下跌的壓力，造成航商難以獲得合理的利潤乃至虧損。有鑑於此，航商必須大幅改變其業務經營方式，導入收益管理的觀念，以克服市場的激烈競爭與波動。收益管理已在航空運輸業行之多年且獲致良好的成效，其主要是利用機位分配與定價的手段獲取航次最大的收益；相對於航空運輸業，定期航運較少使用收益管理有關的系統或模式來執行業務活動。因此，本研究對於收益管理應用在運輸業或其他產業之研究做一完整的整理，分析定期航運之產業問題與發展趨勢，針對其營運特性開發收益管理系統與相關模式，提供航運公司建立與導入收益管理系統之參考。
本研究提出一套定期航運收益管理模式(Liner Shipping Revenue Management, LSRM)，其包括兩個主要部分的功能：(1) 長期規劃 — 包括顧客管理、成本管理、市場監控、航線規劃與船隊排程；(2) 短期營運 — 包括貨載需求預測、艙位分配、定價、貨櫃調度、動態艙位控制；該系統亦必須與運費收入、成本、貨櫃存量等資料庫以及會計系統串連整合。定期航運收益管理以有效的艙位分配與定價方法，考量空櫃調度狀況，配合精確的掌控輸儲成本與市場貨載需求，攬載邊際貢獻較高之貨載，達到艙位分配使用收益之最佳化。
定期航線、船期一旦決定開航後，不易在短期間內改變或停航，因此，在航線開航前必須經過整體的規劃，進行船隊排程與成本分析。在定期航運收益管理系統中，航線規劃與船隊排程的功能可以提供企劃人員規劃新航線、調整或整合航線網路的決策支援，使得航線的貨載潛能達到最大。本研究提供系統分析的方法，利用動態規劃構建船隊排程模式，以及重新釐清在航線規劃時成本分析的各個成本項目，幫助企劃人員在許多的碼頭船席時間窗限制下決定最佳的船隊排程，並且較準確的估計航線固定成本與貨載的變動成本，有助於航線可行性的分析。本動態船隊排程模式所導出的排程策略除了靠港、離港的時間船期外，亦包括港口間的航速與碼頭起重機的調配，而不是暫時排定的粗略船期。此外，本模式可以延伸用以整合航運公司內的航線或是聯盟間的航線網路，讓幅軸式服務網路運作更有效率，縮短轉運時間，增加服務頻次，而且經由模式排定的船期，可因為船舶油耗與停港時間的節省而減少航線成本。
貨櫃船艙位分配為影響定期航運公司收益與船舶容量利用率的重要決策，在面對激烈競爭的市場與貨載運輸需求不確定的情況下，航商應透過更精緻的艙位分配與定價以獲取航次的最大利潤。本研究針對艙位分配的問題，利用數學規劃與模糊多目標規劃方法構建兩個貨櫃船艙位分配模式。考量定期航運貨載變動成本較大的特性，在第一個模式(SA1)目標上採取航次總邊際貢獻(總運費收入減總變動成本)最大化，並加入可能發生空櫃調度成本的運量不平衡因子。另外，第二個模式(SA2)則同時處理在艙位分配時需考慮的兩個目標，亦即航次的貨載邊際貢獻與代理行的滿意度，以及處理貨載運輸需求與貨重的不確定性。模式應用在國內航運公司遠歐航線上，與現行的分配比較結果顯示本模式在艙位分配上不僅可獲得較佳的收益並可兼顧代理行的滿意度，以及考量貨載重量的分配。
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.
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