4 Scheduling of Berthing Resources at a Marine Container Terminal via the use of Genetic Algorithms: Current and Future Research (original) (raw)
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Evolutionary Computation, 2009
The tremendous increase of containerized trade over the last several years, the resulting congestion in container terminals worldwide, the remarkable increase in containership size and capacity, the increased operating cost of container vessels and the adoption by liner shipping companies of yield management techniques strain the relationships between ocean carriers and container terminal operators. Shipping lines want their vessels to be served upon arrival or according to a favorable priority pattern and complete their loading/unloading operations within a prearranged time window, irrespective of the problems and shortage of resources terminal operators are facing. Therefore, allocating scarce seaside resources is considered to be a problem deserving both practical and theoretical attention. Scientific research has focused on scheduling problems dealing primarily with two of the most important seaside resources: berth space and quay cranes. Comprehensive reviews of applications and optimization models in the field of marine container terminal operations are given by , , Steenken et al. (2004, and . Scheduling of berth space, also called the berth scheduling problem (BSP), can be simply described as the problem of allocating space to vessels at the quay in a container terminal. The quay crane scheduling problem (QSP) can be described as the problem of allocating quay cranes to each vessel and vessel section. Vessels arrive at a container terminal over time and the terminal operator assigns them to berths to be served. To unload/load the containers from/onboard the vessel a number of quay cranes are assigned to each vessel. Ocean carriers, and therefore vessels, compete over the available berths and quay cranes, and different factors affect the berthing position, the start time of service, and the number of quay cranes assigned to each vessel. Several formulations have been presented for the BSP, the QSP, and recently for the combination of the BSP and QSP, the berth and quay crane scheduling problem (BQSP). Most of the model formulations have been single objective and it was not until recently that researchers recognized the multi-objective and multi-level character of these problems and introduced formulations that capture berth scheduling policies using the latter two formulations. The formulations that have appeared in the literature, in most cases, lead to NP-hard problems that require a heuristic or meta-heuristic algorithm to be developed in order to obtain a solution within computationally acceptable
Optimal berth allocation and time-invariant quay crane assignment in container terminals
European Journal of Operational Research, 2014
Due to the dramatic increase in the world's container traffic, the efficient management of operations in seaport container terminals has become a crucial issue. In this work, we focus on the integrated planning of the following problems faced at container terminals: berth allocation, quay crane assignment (number), and quay crane assignment (specific). First, we formulate a new binary integer linear program for the integrated solution of the berth allocation and quay crane assignment (number) problems called BACAP. Then we extend it by incorporating the quay crane assignment (specific) problem as well, which is named BACASP. Computational experiments performed on problem instances of various sizes indicate that the model for BA-CAP is very efficient and even large instances up to 60 vessels can be solved to optimality. Unfortunately, this is not the case for BACASP. Therefore, to be able to solve large instances, we present a necessary and sufficient condition for generating an optimal solution of BACASP from an optimal solution of BACAP using a post-processing algorithm. In case this condition is not satisfied, we make use of a cutting plane algorithm which solves BACAP repeatedly by adding cuts generated from the optimal solutions until the aforementioned condition holds. This method proves to be viable and enables us to solve large BACASP instances as well. To the best of our knowledge, these are the largest instances that can be solved to optimality for this difficult problem, which makes our work applicable to realistic problems.
Operations Research Proceedings, 2013
In this work, we focus on the integrated planning of the following problems faced within the context of seaside operations at container terminals: berth allocation, quay crane assignment, and quay crane scheduling. First, we formulate a new binary integer linear program for the integrated solution of the berth allocation and quay crane assignment problems called BACAP. Then we extend it by incorporating the crane scheduling problem as well, which is named BACASP. Although the model for BACAP is very efficient and even large instances up to 60 vessels can be solved to optimality, only small instances for BACASP can be solved optimally. To be able to solve large instances, we present a necessary and sufficient condition for generating an optimal solution of BACASP from an optimal solution of BA-CAP using a postprocessing algorithm. We also develop a cutting plane algorithm for the case where this condition is not satisfied. This algorithm solves BACAP repeatedly by adding cuts generated from the optimal solutions at each trial until the aforementioned condition holds.
A Genetic Algorithm for Berth Allocation and Quay Crane Assignment
Lecture Notes in Computer Science, 2012
Container terminals are facilities where cargo containers are transshipped between different transport vehicles, for onward transportation. They are open systems that carry out a large number of different combinatorial problems that can be solved by means of Artificial Intelligence techniques. In this work, we focus our attention on scheduling a number of incoming vessels by assigning to each a berthing position, a mooring time and a number of Quay Cranes. This problem is known as the Berthing Allocation and Quay Crane Assignment problem. To formulate the problem, we first propose a mixed integer linear programming model to minimize the total weighted service time of the incoming vessels. Then, a meta-heuristic algorithm (Genetic Algorithm (GA)) is presented for solving the proposed problem. Computational experiments are performed to evaluate the effectiveness and efficiency of the proposed method.
European Journal of Operational Research, 2016
There has been a dramatic increase in world's container traffic during the last thirty years. As a consequence, the efficient management of container terminals has become a crucial issue. In this work we concentrate on the integrated seaside operations, namely the integration of berth allocation, quay crane assignment and quay crane scheduling problems. First, we formulate a mixed-integer linear program whose exact solution gives optimal berthing positions and berthing times of the vessels, along with their crane schedules during their stay at the quay. Then, we propose an efficient cutting plane algorithm based on a decomposition scheme. Our approach deals with berthing positions of the vessels and their assigned number of cranes in each time period in a master problem, and seeks the corresponding optimal crane schedule by solving a subproblem. We prove that the crane scheduling subproblem is NP-complete under general cost settings, but can be solved in polynomial time for certain special cases. Our computational study shows that our new formulation and proposed solution method yield optimal solutions for realistic-sized instances.
Optimization Process for Berth and Quay-Crane Assignment in Container Terminals with Separate Piers
Athens Journal of Τechnology & Engineering
The objective of this research is the study of container terminals with two separated piers within the same port basin. The main problem is how to optimize the berth and crane allocation and to minimize the overall service time for the vessels and to improve the utilization of the terminal assets. The optimization of the seaside subsystem of the container terminals combines three typical operational problems: ship-to-berth allocation, quay-crane to ship assignment and quay-crane scheduling. Due to their characteristics, they have a high correlation and should be considered together. The problem can become even more complex in the Container terminals with a different layout where quays and berths are not placed in the line or where berths are situated in different piers. In this paper, a specific methodology is presented with a focus on the optimization process. This process consists of three stages namely: initiation, allocation and adjustment. The core of the problem solutions in stage 1 is the execution of crane scheduling problem according to cargo volume and container distribution on the vessel. The result of this stage is three operational scenarios that set out two key variables: duration of the handling process and the number of cranes required. According to the results from stage 1, ship-to-berth assignment and allocation of cranes isexecuted. The practical approach implemented here, targets to high prediction, reliability and efficiency of the operational plans to satisfy the requirements of the shipping companies. This approach requires a fixed number of quay-cranes during the handling operations and high utilization rate of the cranes. The results of the overall optimization have been shown on the few examples.
Naval Research Logistics (NRL), 2006
In this paper, we study the problem of scheduling quay cranes (QCs) at container terminals where incoming vessels have different ready times. The objective is to minimize the maximum relative tardiness of vessel departures. The problem can be formulated as a mixed integer linear programming (MILP) model of large size that is difficult to solve directly. We propose a heuristic decomposition approach to breakdown the problem into two smaller, linked models, the vessel-level and the berth-level models. With the same berth-level model, two heuristic methods are developed using different vessel-level models. Computational experiments show that the proposed approach is effective and efficient.
Operations Research Proceedings
This paper deals with the combination of two decision problems, which occur consecutively while planning the charge and discharge operations of container ships in container terminals. The Berth Allocation Problem (BAP) considers the allocation of ships to berths in the course of time. The Crane Assignment Problem (CAP) addresses the assignment of quay cranes to ships. We provide a heuristic approach for the integrated solution of these problems and present computational results based on real world data.
Assignment and deployment of quay cranes at a maritime container terminal
2008
The complex logistic process of vessel berthing followed by container discharge/loading, at maritime container terminals (MCTs), is focused in this paper. Discrete-event simulation models are well capable of representing the entire process in a stochastic, dynamic environment. Hence, simulation results to be an effective planning and control tool for decision making and evaluation. The assignment of quay cranes to berthed vessels and their deployment along the berth represent crucial decisions that could be well supported by integer programming (IP) models. Usually, these models are used as standalone tools. Starting from a discrete-event simulator for the berth planning, previously developed for a real maritime container terminal, we propose two IP models that can be embodied within the simulator to verify whether or not the weekly plan of the berth schedule produced by the simulator itself is feasible with respect to the available quay cranes. If not, the manager would be asked to repeat the berth planning step by rerunning simulation. The goodness of the proposed IP formulations is established by a numerical comparison against a test case taken from literature.