مدیریت عملیات پایانه در حمل دریایی خودرو
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|12172||2004||18 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Transportation Research Part A: Policy and Practice, Volume 37, Issue 5, June 2003, Pages 435–452
This paper reports on the development of an automated planning and scheduling system supporting terminal operations of the vehicle transshipment hub in Bremerhaven. We describe terminal operations and derive an integral decision model for manpower planning and inventory control. Thereby we propose a hierarchical separation of the integral model into sub-models and develop heuristics to solve the arising sub-problems.
The logistics of finished vehicles has grown impressively during the last decade, leading to the emergence of a world-wide hub and spoke network (Drewry, 1999). Despite high growth rates, the oligopolistic structure of the market has led to a dramatic increase in competition between ports (MarketLine, 1998). Nowadays, ports must face up to market demands and deliver quality service and improved efficiency (Cullen, 1998). To this end the authors have set out to develop a decision planning and scheduling system intended to support terminal operations at the vehicle transshipment hub in Bremerhaven. Decision-making related to vehicle hub operations can draw on methodological support offered by standard approaches to hub location (Domschke and Krispin, 1997; Racunica and Wynter, 2000), ship routing and scheduling (Ronen, 1993; Fagerholt and Christiansen, 1999; Bendall and Stent, 2001), the design of storage areas (Iranpour and Tung, 1989; Cassady and Kobza, 1998) and, finally, loading issues (Agbegha et al., 1998; Nishimura et al., 2001). As yet, there has been no methodological support available for vehicle terminal operations of the type already developed for container transshipment (Steenken et al., 1993; Chen, 1999; Böse et al., 2000; Shabayek and Yeung, 2002). Terminal operations in vehicle transshipment differ significantly from container transshipment, that is typically supported by rule-based control systems. First, container flows are strongly fragmented, whereas vehicle flows have much in common with bulk cargos. Second, containers may be relocated several times during their stay in a hub. Due to the danger of damage resulting to vehicles, the practice of relocation is avoided at vehicle hubs. Third, containers can be stacked upon one another, increasing storage space, whereas vehicles cannot. In vehicle transshipment, the notion of bulk grouping allows the definition of reasonably sized entities for planning. Since the relocation of vehicles should be kept to a minimum, their assignment to appropriate locations is a matter of importance. Finally, the area taken up by vehicle stocks is enormous, so that the distances to be covered become an important component in the planning process. These findings have motivated the design of a planning and scheduling system, rather than a rule-based control system. In Section 2 we introduce terminal operations and discuss the planning and scheduling problem as it generally occurs in vehicle transshipment. In Section 3 we present an integral optimization model for manpower planning and inventory control. In Section 4 we consider the hierarchical problem separation and the heuristic solution procedures for the separated sub-problems. Finally we discuss the impact on the system’s efficiency in Section 5, before we conclude in Section 6.
نتیجه گیری انگلیسی
In this paper we have described the currently evolving hub and spoke network for the transportation of finished vehicles. The increasing volumes of transshipped vehicles call for planning and scheduling support, particularly for large hubs. In a rolling time horizon, transshipment tasks have to be scheduled that are constrained by inventory capacity and manpower availability. In this paper we have modeled this issue resulting in a complex combinatorial problem. In the following we presented a separation of this problem into a two-stage hierarchical model. For both stages we have proposed heuristic procedures capable of solving the entire problem in an iterative decision support system. First reports of the practical use of the system are encouraging. The system allows the integration of customers into the planning process. In this way supply chain oriented negotiations can be supported. Development continuing in this direction will further strengthen the role of Bremerhaven in finished vehicle logistics.