Decision Problems and Applications of Operations Research at Marine Container Terminals

2011 ◽  
Author(s):  
Anne Goodchild ◽  
Wenjuan Zhao ◽  
Erica Wygonik
Keyword(s):  
Operations Research ◽  
Container Terminals ◽  
Decision Problems ◽  
Marine Container Terminals

scholarly journals Innovative Metaheuristic Algorithms for Efficient Berth Scheduling at Marine Container Terminals; Masoud Kavoosi; Dissertation; 2019

2020 ◽  
Author(s):  
Masoud Kavoosi
Keyword(s):  
Global Economy ◽  
Critical Role ◽  
Turnaround Time ◽  
Liner Shipping ◽  
Container Terminals ◽  
Metaheuristic Algorithms ◽  
Decision Problems ◽  
Computational Time ◽  
Marine Container Terminals ◽  
Berth Scheduling

International trade plays a critical role for the global economy. A significant portion of general consumption goods is transported by vessels in a containerized form. Increasing volumes of the containerized trade impose additional pressure on marine container terminals (MCTs), which are responsible for service of incoming vessels from different liner shipping companies. MCTs are considered as important nodes in supply chains, as they allow transfer of containers from vessels to one of the alternative inland modes (generally, truck or rail). Managing operations within MCTs is a quite challenging task not only due to increasing seaborne trade volumes, but also due to increasing number of liner shipping alliances, deployment of megaships by liner shipping companies, inability to expand the terminal size due to spatial constraints, and other factors. Another important goal for the MCT operator is to ensure the timely service of vessels, as the vessel service delays may result in potential disruption of liner shipping schedules, and ultimately cause product delivery delays to the final customers.This dissertation focuses on addressing complex decision problems, which are faced by the MCT operators. The seaside operations, which deal with loading and unloading of vessels, will be of a primary interest, as they affect the total turnaround time of vessels. The latter is considered as one of the key performance indicators for the MCT operations. As many of decision problems related to the seaside operations, cannot be solved using the exact optimization algorithms (e.g., Simplex, Branch-and-Bound, Brach-and-Cut) within a reasonable computational time for the realistic size problem instances, a number of metaheuristic algorithms will be proposed (with a primary focus on Evolutionary Algorithms, which have been widely used in different fields for solving combinatorial decision problems). The proposed metaheuristic algorithms are expected to serve as efficient decision making tools for the MCT operators and facilitate exchange of freight flows between water and inland transportation modes.

scholarly journals Berth scheduling at marine container terminals

2019 ◽  
Vol 5 (1) ◽  
pp. 30-66 ◽  
Author(s):  
Masoud Kavoosi ◽  
Maxim A. Dulebenets ◽  
Olumide Abioye ◽  
Junayed Pasha ◽  
Oluwatosin Theophilus ◽  
...  
Keyword(s):  
Population Based ◽  
Container Terminals ◽  
Metaheuristic Algorithms ◽  
Computational Time ◽  
Scheduling Problem ◽  
Metaheuristic Algorithm ◽  
Content Type ◽  
Marine Container Terminals ◽  
Problem Instances ◽  
Berth Scheduling

Purpose Marine transportation has been faced with an increasing demand for containerized cargo during the past decade. Marine container terminals (MCTs), as the facilities for connecting seaborne and inland transportation, are expected to handle the increasing amount of containers, delivered by vessels. Berth scheduling plays an important role for the total throughput of MCTs as well as the overall effectiveness of the MCT operations. This study aims to propose a novel island-based metaheuristic algorithm to solve the berth scheduling problem and minimize the total cost of serving the arriving vessels at the MCT. Design/methodology/approach A universal island-based metaheuristic algorithm (UIMA) was proposed in this study, aiming to solve the spatially constrained berth scheduling problem. The UIMA population was divided into four sub-populations (i.e. islands). Unlike the canonical island-based algorithms that execute the same metaheuristic on each island, four different population-based metaheuristics are adopted within the developed algorithm to search the islands, including the following: evolutionary algorithm (EA), particle swarm optimization (PSO), estimation of distribution algorithm (EDA) and differential evolution (DE). The adopted population-based metaheuristic algorithms rely on different operators, which facilitate the search process for superior solutions on the UIMA islands. Findings The conducted numerical experiments demonstrated that the developed UIMA algorithm returned near-optimal solutions for the small-size problem instances. As for the large-size problem instances, UIMA was found to be superior to the EA, PSO, EDA and DE algorithms, which were executed in isolation, in terms of the obtained objective function values at termination. Furthermore, the developed UIMA algorithm outperformed various single-solution-based metaheuristic algorithms (including variable neighborhood search, tabu search and simulated annealing) in terms of the solution quality. The maximum UIMA computational time did not exceed 306 s. Research limitations/implications Some of the previous berth scheduling studies modeled uncertain vessel arrival times and/or handling times, while this study assumed the vessel arrival and handling times to be deterministic. Practical implications The developed UIMA algorithm can be used by the MCT operators as an efficient decision support tool and assist with a cost-effective design of berth schedules within an acceptable computational time. Originality/value A novel island-based metaheuristic algorithm is designed to solve the spatially constrained berth scheduling problem. The proposed island-based algorithm adopts several types of metaheuristic algorithms to cover different areas of the search space. The considered metaheuristic algorithms rely on different operators. Such feature is expected to facilitate the search process for superior solutions.

Has Dynamic Programming Improved Decision Making?

2019 ◽  
Vol 11 (1) ◽  
pp. 833-858 ◽  
Author(s):  
John Rust
Keyword(s):  
Decision Making ◽  
Dynamic Programming ◽  
Real World ◽  
Operations Research ◽  
Decision Rules ◽  
Decision Problems ◽  
Optimal Decision ◽  
Sequential Decision ◽  
Success Stories ◽  
Real World Applications

Dynamic programming (DP) is a powerful tool for solving a wide class of sequential decision-making problems under uncertainty. In principle, it enables us to compute optimal decision rules that specify the best possible decision in any situation. This article reviews developments in DP and contrasts its revolutionary impact on economics, operations research, engineering, and artificial intelligence with the comparative paucity of its real-world applications to improve the decision making of individuals and firms. The fuzziness of many real-world decision problems and the difficulty in mathematically modeling them are key obstacles to a wider application of DP in real-world settings. Nevertheless, I discuss several success stories, and I conclude that DP offers substantial promise for improving decision making if we let go of the empirically untenable assumption of unbounded rationality and confront the challenging decision problems faced every day by individuals and firms.

Evaluation of the floaterm concept at marine container terminals via simulation

2015 ◽  
Vol 54 ◽  
pp. 19-35 ◽  
Author(s):  
M.A. Dulebenets ◽  
M.M. Golias ◽  
S. Mishra ◽  
W.C. Heaslet
Keyword(s):  
Container Terminals ◽  
Marine Container Terminals

Vehicle Sequencing at Transshipment Terminals with Handover Relations

2020 ◽  
Author(s):  
Dirk Briskorn ◽  
Malte Fliedner ◽  
Martin Tschöke
Keyword(s):  
Exact Solution ◽  
Computational Study ◽  
Solution Algorithm ◽  
Comprehensive Analysis ◽  
Container Terminals ◽  
Decision Problems ◽  
Operational Planning ◽  
Vast Number ◽  
Synchronization Problem ◽  
Structural Connections

Operational planning at transshipment nodes is a wide and challenging field of research that covers a vast number of distinct relevant applications, spanning from seaport container terminals to rail terminals to cross-docks. In this work, we study the feasibility version of a fundamental synchronization problem that assigns incoming vehicles to docking resources subject to handover relations. We carry out a comprehensive analysis of computational complexity of various problem variants and establish structural connections to famous decision problems in graph theory. We further propose an exact solution algorithm for finding feasible dock assignments, if vehicles can visit the node only once and evaluate its performance in a comprehensive computational study.

scholarly journals A novel continuous berth scheduling model at multiple marine container terminals with tidal considerations

2017 ◽  
Vol 2 (2) ◽  
pp. 142-157 ◽  
Author(s):  
Ali Dadashi ◽  
Maxim A. Dulebenets ◽  
Mihalis M. Golias ◽  
Abdolreza Sheikholeslami
Keyword(s):  
Mathematical Model ◽  
Time Of Day ◽  
Container Terminals ◽  
Channel Depth ◽  
Content Type ◽  
Access Channel ◽  
Marine Container Terminals ◽  
Bandar Abbas ◽  
Berth Scheduling ◽  
Operational Data

Purpose The paper aims to propose a new mathematical model for allocation and scheduling of vessels at multiple marine container terminals of the same port, considering the access channel depth variations by time of day. Design/methodology/approach This paper proposes a new mathematical model for allocation and scheduling of vessels at multiple marine container terminals of the same port, considering the access channel depth variations by time of day. The access channel serves as a gate for vessels entering or leaving the port. During low-depth tidal periods the vessels with deep drafts have to wait until the depth of the access channel reaches the required depth. Findings A number of numerical experiments are performed using the operational data collected from Port of Bandar Abbas (Iran). Results demonstrate that the suggested methodology is able to improve the existing port operations and significantly decrease delayed vessel departures. Originality/value The contribution of this study to the state of the art is a novel mathematical model for allocation and scheduling of vessels at multiple terminals of the same port, taking into consideration channel depth variations by time of day. To the best of the authors’ knowledge, this is the first continuous berth scheduling linear model that addresses the tidal effects on berth scheduling (both in terms of vessel arrival and departure at/from the berth) at multiple marine container terminals.

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