Priority control of berth allocation problem in container terminals

Ann Oper Res DOI 10.1007/s10479-015-1912-7 Priority control of berth allocation problem in container terminals Evrim Ursavas1 © The Author(s) 2015. This article is published with open access at Springerlink.com Abstract This paper presents a decision support system for the core problem of berth allocation decision in a container terminal. The allocation of berths to the calling vessels is complex with the fact that different service level requirements are required for different vessels. Terminal managers demand for effective decision support systems that would aid them with the allocation problem considering service priorities. Consequently, this study provides a DSS, built by a dynamic discrete-event simulation model embedded with an optimization tool that determines the priority controls for the berth allocation to the calling vessels. To show the practical application of the DSS, a comprehensive case study from a Turkish container terminal considering the current state and future expansion plans that also provides an indication of the usability aspect of the program on other ports around the world has been conducted. Further experiments are conducted based on data from the Port of Rotterdam. The DSS presented in this study may help port authorities in determining more efficient allocation decisions within a container terminal. Keywords Port management · Simulation optimization · Berth allocation · Container terminal operations 1 Introduction With the high demand of sea trade, container transportation has been the core of modern logistics, and container terminals are considered as key nodes of international transportation. Container terminals are complex dynamic systems intertwined with many activities. Among those operations berth allocation problem can be considered as one of the major issues as it is this operation that drives the whole port management process. When a vessel arrives at a port, it must be anchored at a specified berth by the terminal planners. In Multi-User Terminals B Evrim Ursavas 1 Department of Operations, Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands 123 Ann Oper Res (MUT) where berths are dynamically allocated to calling vessels and are not always assigned to specific berth locations such as in Dedicated Terminals (DT), berth planning becomes the root of all operations. An inefficient decision in the berth allocation phase affects all the other applications connected to this and may increase the service period and costs. Existing literature has demonstrated that employing flexible vessel-berth-order allocation without taking into account the First-Come-First-Served (FCFS) rule, higher productivity can be obtained (Imai et al. 2008). Following the FCFS rule and treating every vessel without any differentiated priority may have severe results up to the loss of current leading customers. Terminal managers are therefore enforced to operate their berths under intelligent strategies. In practice, vessels with high container volume prefer to be given priority over small vessels. In general the ship priority depends on the total throughput per shipping line. Accordingly, the ship size can be regarded as a variable for the priority index which is often closely correlated to the significance of the shipping company (Imai et al. 2003). However, terminal operators must also consider the issue of smaller vessels where they may be dominated by large vessels having much higher handling times. From the above discussions, it is apparent that a decision support tool that would help terminal operators in making efficient berth allocation decisions under dynamic terminal settings is of high necessity. The contribution of this article consists of providing terminal managers a decision support tool, convenient for use in different type of berth layouts, for the berth allocation problem considering service level differentiations amongst vessels. The DSS employs an architecture to generate solutions for the user intervened problem cases. Given the importance of stochastic nature of the container terminal operations, a discrete event simulation model, with an embedded optimization module based on meta-heuristics, is developed for the core component of the decision support system. The remainder of this paper is organized as follows: Following section will put forward the related literature. The problem will be explained in detail in Sect. 3. Next, proposed system structure will be presented. Subsequently, system applications and analysis will be presented. Finally, the last section will be devoted to concluding remarks and future work. 2 Literature review The need for effective decision making strategies for managing container terminal operations has become certainly obvious and therefore the area has attracted many researchers into the subject (Carlo et al. 2013; Vis and Koster 2003; Steenken et al. 2004; Stahlbock and Voß 2008). In this review, studies handling berth allocation problem considering vessel priorities will be summarized first. Next, studies that capture the stochastic nature of the problem will be put forward. Last, previous literature on decision support systems developed for use in container terminals will be presented. With regard to the studies dealing with the berth allocation problem and together considering different levels of vessel priorities, Imai et al. (2003) employed a genetic algorithm based heuristic to solve the nonlinear problem by defining priorities through assigning weights to the vessels related by their handling volumes within the objective function. Hansen et al. (2008) imposed ship dependent premiums and penalty costs for handling priority issues and aimed to minimize total costs made up of waiting, handling, earliness and lateness costs. In Imai et al. (2007), a bi-objective berth allocation problem where weights are employed to distinguish between the dissimilar vessel priorities minimizing vessel delays and total service time is presented. Saharidis et al. (2010) categorized the vessels as preferential or 123 Ann Oper Res non-preferential and have considered the maximization of preferential customer satisfaction to be more important than port’s total throughput. They used hierarchical optimization framework, using hierarchical structure that distinguishes between two contradictory objectives port managers come across for the berth allocation problem. Guan et al. (2002) assigned weights to the vessels according to their sizes which were used within the objective function where the aim was to minimize the total weighted completion time of vessel service. Guan and Cheung (2004) defined a weight coefficient for each vessel and they optimized the total weighted flow time using a method that combines tree procedure and a heuristic. Study by Cordeau et al. (2005) is based on multi depot vehicle routing problem with time windows in which the objective is the minimization of (...truncated)