軸輻貨櫃海運網路之路線、船型與頻次決策研究

Abstract

貨櫃運送路線、船型與頻次決策是航商最重要的航運規劃課題之一，規劃結果不僅影響航商的營運效率，亦影響其提供給貨主的服務品質。由於貨櫃航運服務的同質性高，航商在競爭激烈環境中除了考慮自身航運成本，尚須同時增進服務品質以提升競爭力，才是較佳的航運規劃。基於存貨成本是影響航運服務品質的重要因素，貨主常依存貨成本直接相關的航線頻次、貨櫃運送時間來選擇航運服務，本研究提出以航運成本與存貨成本最小化之雙目標，探討軸輻海運網路下貨櫃運送之路線、船型與頻次決策。 首先，本研究以解析性方法構建航運成本函數與存貨成本函數。然後，由兩成本間的替換關係推導航運成本與存貨成本的數學關係式，在目標值空間上決定雙目標最小化之柏拉圖最佳解，可求得一航線在不同存貨成本與航運成本值之最適船型與頻次，並得到軸輻海運網路貨櫃轉運或直接運送之路線決策。此外，本研究推導出船型決策臨界點隨貨物載運量變動的數學關係式，以圖示顯示船型決策隨貨物載運量增加而傾向採用較具規模經濟性之大型船，並在目標值空間上顯示存貨成本、船舶規模經濟性與航速在決策中的影響。最後，蒐集船舶與港埠成本資料進行範例分析，以驗證理論推導結果、闡述模式實用價值。 研究結果求得一航線在不同存貨成本與航運成本水準下的最適船型與頻次，亦求得軸輻網路貨物轉運或直接運送之路線決策，並分析得到重要因素在決策中的影響。除以圖示顯示船型決策隨貨物載運量增加而傾向採用大型船外，亦分析超大型船投入營運之經濟營運載運量，驗證提高港埠效率、增長航程、減少靠港數目或降低大型船的相對成本有助於提高超大型船的航運經濟性。此外，路線決策之範例分析結果與目前航運現況相符，敏感度分析可闡述實務上貨物載運量增加有利於直接運送、軸心港費率下降或作業效率提升有吸引貨物轉運之特性。綜之，運用雙目標模式可增加航商決策之彈性，以獲得較佳的規劃結果，並可協助航商估算各航線引入超大型船之最佳時機。

Decision-making on routing, ship size, and sailing frequency are important issues for container carriers when planning shipping services. The results of those decisions directly influence the operating effectiveness of container carriers and the quality of service provided to shippers. Since container carriers operate in an increasingly competitive environment, they not only aim at lowering their shipping costs, but also at enhancing their services in order to increase their competitiveness. Inventory costs related to the container shipping process are crucial factors affecting the quality of service provided to shippers. Therefore, this study formulates a two-objective model to determine the optimal routing, ship size, and sailing frequency for container carriers by minimizing shipping costs and inventory costs. First, shipping and inventory cost functions are formulated using an analytical method. Then, based on a trade-off between shipping costs and inventory costs, Pareto optimal solutions of the two-objective model are determined in objective value space. Not only can the optimal ship size and sailing frequency be determined for any route, but also the routing decision on whether to routing containers through a hub or directly to its destination can be made. Moreover, a relationship between the optimal ship size and cargo flow is derived to show that the optimal ship tends to be large as cargo flow increases. The effects of inventory costs, economies of ship size, and service speed on routing, ship size, and sailing frequency decisions are also illustrated. Finally, case studies are made to confirm the theoretical findings and to demonstrate the usefulness of the proposed model. The results show the optimal routing, ship size, and sailing frequency with respect to each level of inventory costs and shipping costs, and the effects of key factors on those decisions. The optimal ship tends to be large as route flow increases, and the minimum route flow that realizes scale economies for ultra large ships can be estimated. Furthermore, the economies and possibility of using ultra large ships tend to increase, as port efficiency improves, shipping distance increases, the number of ports of calls decreases, or the relative costs of large ships decrease. Besides, the results of case studies are reasonable and in accordance with the real world routing decision of current carriers. Sensivitity analysis shows that the optimal routing decision tends to be shipping the cargo directly as the flow increases, and shipping it through a hub as the hub charge is decreased or its efficiency is improved. In sum, the two-objective model can provide flexibility in the decision-making for container carriers to produce better planning alternatives. It can also guide carriers to find the optimal timing of using ultra large ships.