Marine Container Terminal Operators Research Articles

Berth allocation and scheduling at marine container terminals: A state-of-the-art review of solution approaches and relevant scheduling attributes

AbstractMarine container terminals play a significant role for international trade networks and global market. To cope with the rapid and steady growth of the seaborne trade market, marine container terminal operators must address the operational challenges with appropriate analytical methods to meet the needs of the market. The berth allocation and scheduling problem is one of the important decisions faced by operators during operations planning. The optimization of a berth schedule is strongly associated with the allocation of spatial and temporal resources. An optimal and robust berth schedule remarkably improves the productivity and competitiveness of a seaport. A significant number of berth allocation and scheduling studies have been conducted over the last years. Thus, there is an existing need for a comprehensive and critical literature survey to analyze the state-of-the-art research progress, developing tendencies, current shortcomings, and potential future research directions. Therefore, this study thoroughly selected scientific manuscripts dedicated to the berth allocation and scheduling problem. The identified studies were categorized based on spatial attributes, including discrete, continuous, and hybrid berth allocation and scheduling problems. A detailed review was performed for the identified study categories. A representative mathematical formulation for each category was presented along with a detailed summary of various considerations and characteristics of every study. A specific emphasis was given to the solution methods adopted. The current research shortcomings and important research needs were outlined based on the review of the state-of-the-art. This study was conducted with the expectation of assisting the scientific community and relevant stakeholders with berth allocation and scheduling.

An augmented self-adaptive parameter control in evolutionary computation: A case study for the berth scheduling problem

The demand for international seaborne trade has substantially increased over the last three decades and is predicted to continue increasing during the upcoming years. A marine container terminal, as an important node in supply chains, should be able to successfully cope with increasing demand volumes. Berth scheduling can significantly influence the general throughput of marine container terminals. In this study, a mixed-integer linear programming mathematical model is proposed for the berth scheduling problem, aiming to minimize the summation of waiting costs, handling costs, and late departure costs of the vessels that are to be served at a marine container terminal. An innovative Evolutionary Algorithm is designed to solve the developed mathematical model. The proposed solution algorithm relies on the augmented self-adaptive parameter control strategy, which is developed in order to effectively change the algorithmic parameters throughout the search process. Performance of the designed algorithm is evaluated against nine alternative state-of-the-art metaheuristic-based algorithms, which have been frequently used for berth scheduling in the marine container terminal operations literature. The results demonstrate that all the developed algorithms have a high level of stability and return competitive solutions at convergence. The computational experiments also prove superiority of the designed augmented self-adaptive Evolutionary Algorithm over the alternative algorithms in terms of different performance indicators.

An Adaptive Island Evolutionary Algorithm for the berth scheduling problem

Increasing volumes of the seaborne containerized trade put additional pressure on marine container terminal operators. Long congestion periods have been reported at certain marine container terminals due to inability of the infrastructure to serve the growing demand, increasing number of megaships, port disruptions, and other factors. In order to alleviate congestion and avoid potential cargo delivery delays to the end customers, marine container terminal operators have to enhance the efficiency of their operations. This study focuses on improving the seaside operations at marine container terminals. A new Adaptive Island Evolutionary Algorithm is proposed for the berth scheduling problem, aiming to minimize the total weighted service cost of vessels. The developed algorithm simultaneously executes separate Evolutionary Algorithms in parallel on its islands and exchanges individuals between the islands based on an adaptive mechanism, which allows more efficient exploration of the problem search space. A set of extensive computational experiments indicate that the optimality gaps of the Adaptive Island Evolutionary Algorithm do not exceed 1.93% for the considered small-size problem instances. Furthermore, the proposed solution algorithm was compared against the other state-of-the-art metaheuristic algorithms and exhibited statistically significant improvements in terms of the objective function values.

A Self-Adaptive Evolutionary Algorithm for the Berth Scheduling Problem: Towards Efficient Parameter Control

Since ancient times, maritime transportation has played a very important role for the global trade and economy of many countries. The volumes of all major types of cargo, which are transported by vessels, has substantially increased in recent years. Considering a rapid growth of waterborne trade, marine container terminal operators should focus on upgrading the existing terminal infrastructure and improving operations planning. This study aims to assist marine container terminal operators with improving the seaside operations and primarily focuses on the berth scheduling problem. The problem is formulated as a mixed integer linear programming model, minimizing the total weighted vessel turnaround time and the total weighted vessel late departures. A self-adaptive Evolutionary Algorithm is proposed to solve the problem, where the crossover and mutation probabilities are encoded in the chromosomes. Numerical experiments are conducted to evaluate performance of the developed solution algorithm against the alternative Evolutionary Algorithms, which rely on the deterministic parameter control, adaptive parameter control, and parameter tuning strategies, respectively. Results indicate that all the considered solution algorithms demonstrate a relatively low variability in terms of the objective function values at termination from one replication to another and can maintain the adequate population diversity. However, application of the self-adaptive parameter control strategy substantially improves the objective function values at termination without a significant impact on the computational time.

The evaluation of the attractiveness of marine container terminal sector: analysing the polish sector

The importance of attractiveness of the marine container terminal operators have significantly increased in the recent years due to them influence on the worldwide economy. This article aim is to evaluate the attractiveness of marine container terminals by using a qualitative analysis. The main point is to define the attractiveness of the Marine Container Terminal Operators (MCTOs) located in Poland. The qualitative analysis has provided arguments to conclude that marine container market in Poland currently is attractive from the point of existing MCTOs in this sector. The developed model helps to estimate the attractiveness of the marine container terminal market (MCTM) in Poland.

Application of Evolutionary Computation for Berth Scheduling at Marine Container Terminals: Parameter Tuning Versus Parameter Control

Considering a substantial increase in the international seaborne containerized trade volumes, marine container terminal operators have to improve efficiency of the processes inside their terminals in order to meet the growing demand. An efficient berth scheduling is of a high importance for the terminal’s performance, as it significantly influences the turnaround time of vessels. This paper proposes a novel Evolutionary Algorithm to assist with berth scheduling at marine container terminals that, unlike published to date studies on berth scheduling, applies a parameter control strategy. Specifically, an adaptive mechanism is developed for the mutation operator, in which the mutation rate is altered based on feedback from the search. The objective of the proposed mixed integer model aims to minimize the total weighted vessel service cost. A set of numerical experiments are conducted to assess performance of the developed algorithm based on a comparison against a typical Evolutionary Algorithm that applies a constant mutation rate value, determined from the parameter tuning analysis. Results indicate that the optimality gap does not exceed 0.80% for both algorithms. Furthermore, deployment of the adaptive mechanism for the mutation operator yields an average of 5.4% and 8.5% savings in terms of the total weighted vessel service cost for medium and large size problem instances, respectively, without a significant increase in the computational time.

A novel memetic algorithm with a deterministic parameter control for efficient berth scheduling at marine container terminals

Purpose The volumes of international containerized trade substantially increased over the past years. In the meantime, marine container terminal (MCT) operators are facing congestion issues at their terminals because of the increasing number of large-size vessels, the lack of innovative technologies and advanced handling equipment and the inability of proper scheduling of the available resources. This study aims to propose a novel memetic algorithm with a deterministic parameter control to facilitate the berth scheduling at MCTs and minimize the total vessel service cost. Design/methodology/approach A local search heuristic, which is based on the first-come-first-served policy, is applied at the chromosomes and population initialization stage within the developed memetic algorithm (MA). The deterministic parameter control strategy is implemented for a custom mutation operator, which alters the mutation rate values based on the piecewise function throughout the evolution of the algorithm. Performance of the proposed MA is compared with that of the alternative solution algorithms widely used in the berth scheduling literature, including a MA that does not apply the deterministic parameter control strategy, typical evolutionary algorithm, simulated annealing and variable neighborhood search. Findings Results demonstrate that the developed MA with a deterministic parameter control can obtain superior berth schedules in terms of the total vessel service cost within a reasonable computational time. Furthermore, greater cost savings are observed for the cases with high demand and low berthing capacity at the terminal. A comprehensive analysis of the convergence patterns indicates that introduction of the custom mutation operator with a deterministic control for the mutation rate value would provide more efficient exploration and exploitation of the search space. Research limitations/implications This study does not account for uncertainty in vessel arrivals. Furthermore, potential changes in the vessel handling times owing to terminal disruptions are not captured. Practical implications The developed solution algorithm can serve as an efficient planning tool for MCT operators and assist with efficient berth scheduling for both discrete and continuous berthing layout cases. Originality/value The majority of studies on berth scheduling rely on the stochastic search algorithms without considering the specific problem properties and applying the guided search heuristics. Unlike canonical evolutionary algorithms, the developed algorithm uses a local search heuristic for the chromosomes and population initialization and adjusts the mutation rate values based on a deterministic parameter control strategy for more efficient exploration and exploitation of the search space.

A comprehensive multi-objective optimization model for the vessel scheduling problem in liner shipping

The international seaborne trade volumes have been continuously increasing over the last years. Many liner shipping companies started consolidation to form stronger alliances and attract new customers. In order to remain competitive and avoid potential monetary losses, liner shipping companies have to improve efficiency of their vessel schedules. Some of the decisions that have to be made by liner shipping companies are conflicting in their nature. However, the existing vessel scheduling models generally combine the conflicting objectives into one objective function, which aims to minimize the total route service cost. Such approach imposes limitations for liner shipping companies in the analysis of tradeoffs between the conflicting objectives. To avoid the latter drawback, this study proposes a multi-objective mixed integer nonlinear optimization model for the vessel scheduling problem, which accounts for all major route service cost components reported in the literature and separates them in two conflicting groups. The original mixed integer nonlinear model is linearized by discretizing the vessel sailing speed reciprocal, and the Global Multi-Objective Optimization Algorithm is developed to solve the linearized model. A set of numerical experiments are conducted for the Asia-Mediterranean Express Service liner shipping route. Results demonstrate that negotiation of both vessel service time windows and handling rates between liner shipping companies and marine container terminal operators may significantly reduce the total route service cost components. Furthermore, vessel schedules are found to be more sensitive to the unit fuel cost as compared to the unit carbon dioxide emission cost.

Green vessel scheduling in liner shipping: Modeling carbon dioxide emission costs in sea and at ports of call

Abstract Considering a substantial increase in volumes of the international seaborne trade and drastic climate changes due to carbon dioxide emissions, liner shipping companies have to improve planning of their vessel schedules and improve energy efficiency. This paper presents a novel mixed integer non-linear mathematical model for the green vessel scheduling problem, which directly accounts for the carbon dioxide emission costs in sea and at ports of call. The original non-linear model is linearized and then solved using CPLEX. A set of numerical experiments are conducted for a real-life liner shipping route to reveal managerial insights that can be of importance to liner shipping companies. Results indicate that the proposed mathematical model can serve as an efficient planning tool for liner shipping companies and may assist with evaluation of various carbon dioxide taxation schemes. Increasing carbon dioxide tax may substantially change the design of vessel schedules, incur additional route service costs, and improve the environmental sustainability. However, the effects from increasing carbon dioxide tax on the marine container terminal operations are found to be very limited.

Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms

Considering a rapidly increasing seaborne trade and drastic climate changes due to emissions, produced by oceangoing vessels and container handling equipment, marine container terminal operators not only have to improve effectiveness of their operations to serve the increasing demand, but also to account for the environmental impact associated with the terminal operations. This paper proposes a novel mixed integer mathematical model for the berth scheduling problem, which minimizes the total service cost of vessels, including the total carbon dioxide emission cost due to container handling. The latter pollutant is a primary greenhouse gas that causes global warming. A Hybrid Evolutionary Algorithm, which deploys a set of local search heuristics, is developed to solve the problem. Computational experiments showcase that the optimality gap of the proposed solution algorithm does not exceed 1.61%. It is further shown that the application of additional local search heuristics allows efficient discovery of promising solutions throughout the search process. Results from numerical experiments also indicate that changes in the carbon dioxide emission cost may significantly affect the design of berth schedules. The developed mathematical model and the proposed solution algorithm can thus be adopted as effective planning tools by the marine container terminal operators and improve the environmental sustainability of the terminal operations.

A New Simulation Model for a Comprehensive Evaluation of Yard Truck Deployment Strategies at Marine Container Terminals

Taking into account increasing volumes of the international seaborne trade and increasing port congestion, marine container terminal operators have to improve efficiency of their operations in order to provide timely service of vessels and avoid product delivery delays to customers. This paper focuses on improvement of container transfer operations between the seaside and the marshaling yard and proposes five yard truck deployment strategies. Performance of the considered marine container terminal is evaluated under each one of the yard truck deployment strategies via simulation. Different performance indicators are estimated to determine how the suggested yard truck deployment strategies will affect all equipment types, involved in container handling and transfer. Results from the extensive simulation experiments showcase that all five yard truck deployment strategies provide similar values of vessel service and quay crane performance indicators, while the shortest distance based yard truck deployment strategy yields superior gantry crane and yard truck performance indicators. The worst values of performance indicators are recorded for the random yard truck deployment strategy. Furthermore, the developed simulation model can serve as an efficient planning tool for marine container terminal operators and enhance productivity of the available equipment.

RETRACTED ARTICLE: The fleet deployment problem with variable vessel sailing speeds and port handling times

Liner shipping companies and marine container terminals have to improve efficiency of their operations to remain competitive and be able to serve the increasing demand. To achieve this goal several options exist that include deployment of larger vessels, slow steaming, alliance agreements, construction of new ports, introduction of new types of equipment, and improvement of work organization. This paper proposes and models a new type of service policy agreement between liner shipping companies and marine container terminal operators. According to this agreement each terminal operator offers a set of port handling rates to the liner shipping company. The proposed model minimizes the liner shipping company’s total route service cost by selecting the optimal handling rate at each port and the optimal vessel speed between each port of call on the port rotation. A new method is proposed to estimate the bunker consumption using a linearized version of the non-linear model. Numerical experiments demonstrate efficiency of the solution approach and substantial cost savings for the liner shipping company from the proposed service policy agreement.

Evaluation of the floaterm concept at marine container terminals via simulation

International seaborne trade rose significantly during the past decades. This created the need to increase capacity of existing marine container terminals to meet the growing demand. The major objective of this paper is to evaluate the floaterm concept using simulation modeling and determine if it can improve terminal productivity. The main difference between floaterm and conventional marine container terminals is that, in the former case, transshipment containers are handled by off-shore quay cranes and stored on container barges. Two terminal configurations performance is compared (vessel handling times and equipment utilization) under normal and disruptive conditions. Computational experiments confirm preliminary expectations that the floaterm concept can enhance efficiency of marine container terminal operations under normal and disruptive conditions.

A Six Sigma framework for marine container terminals

PurposeThis research uses an optimisation model, based on the Six Sigma methodology, which assists marine container terminal operators to minimize trucks' congestions, as a defect in the global containerisation and smoothing the gate activity to reduce trucks' turn‐around times. The main purpose of this paper is implementing the Six Sigma in the landside of marine container terminals to reduce the average number of trucks in queues and average trucks' waiting times in both entrance and exit gates.Design/methodology/approachThis study examines the applicability of the DMAIC method along with the SIPOC, cause and effect diagram, and failure mode and effect analysis (FMEA).FindingsIn this paper, Six Sigma methodology is found as an accurate optimisation tool in marine container terminals. Risk Priority Numbers obtained from the FMEA analysis denote that additional control procedures and associated inspections are needed as monitoring tools on the working time and activity of weighbridge operators and truck's drivers. In addition, serious consideration should be given to operator's performance appraisal and improving the administrative systems.Research limitations/implicationsThis study was carried out with some boundaries; like the complex operational system in marine container terminals, available data, time constraints, training the team members and controlling the implemented obtained results.Originality/valueTo date, no study has adequately examined the Six Sigma methodology in marine container terminals as an optimisation tool for reducing trucks' congestion. The challenging issues inherent this problem and the limitation of existing research, motivates this study.

Method of Assessing the Impact of Polish Container Terminals in Reducing the External Costs of Transport

The paper attempts to identify the social costs and benefits of marine container terminal operations regarding feeder vessels services. It presents a method of valuation which takes into account the external costs of additional factors: the nature and direction of the shipping lines operated by the terminals and the size of port hinterland. Based on the proposed method, the impact of container terminals to reduce the external costs of transport has been assessed.