Improving Productivity in U.S. Marine Container Terminals

10.17226/926 ◽  
1986 ◽  
Keyword(s):  
Container Terminals ◽  
Marine Container Terminals

A combined extent fuzzy AHP and simulation method for selecting stacking layout type in marine container terminals

2012 ◽  
Vol 12 (3) ◽  
pp. 332
Author(s):  
Ali Reza Moazen Jahromi ◽  
Amir Saeed Nooramin ◽  
Aboozar Adljooy Safaei
Keyword(s):  
Fuzzy Ahp ◽  
Simulation Method ◽  
Container Terminals ◽  
Marine Container Terminals

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.

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

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.

A fuzzy AHP decision support system for selecting yard cranes in marine container terminals

2011 ◽  
Vol 10 (2) ◽  
pp. 227-240 ◽  
Author(s):  
Mansoor Kiani Moghadam ◽  
Ali Reza Moazen Jahromi ◽  
Amir Saeed Nooramin
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Ahp ◽  
Container Terminals ◽  
Marine Container Terminals
Sign in / Sign up

Export Citation Format

Share Document