An uncertainty-aware AGV assignment algorithm for automated container terminals

This paper studies job assignments for automated guided in container terminal settings under various conditions of uncertainty. An introduction to their operation is provided, along with a flexible dispatching algorithm, suitable for real-time control of AGVs. Using these concepts a new AGV dispatching approach is developed, capable of operating under uncertain conditions within a detailed container terminal model. Several performance indicators are presented, focused on generic features of vehicle operations as well the assessment of uncertainty levels inside the terminal. From the results of the simulation experiments, it is found that the proposed technique outperforms well known heuristics and alternative algorithms.     

Storage pricing strategies for import container terminals under stochastic conditions

This paper presents a model for determining the optimal storage pricing schedule for import containers. A generic schedule which is characterized by a flat rate and a storage time charge is adopted. The model considers analytically the stochastic behavior of the storage yard, as input/output flows are random variables, and includes the migration to an off-dock warehouse. Two objective functions are proposed: maximizing terminal operator profits and minimizing total integrated cost of the system. Some numerical experiments are provided and a sensitivity analysis is performed to investigate the effect of main variables and approaches on the optimal solution.     

Optimization of loading sequence and rehandling strategy for multi-quay crane operations in container terminals

In this paper, we consider the optimization of loading sequence and rehandling strategy in the terminal operation. We present an optimization strategy to minimize the number of rehandles, and establish a mathematical model to integrate the loading sequence and the rehandling strategy under the parallel operation of multi-quay cranes. Furthermore, we give an improved genetic algorithm to solve the model. We show the efficiency of the optimization strategy and algorithm by comparing them with previous strategies and heuristics.     

Modeling the mixed storage strategy for quay crane double cycling in container terminals

A mixed storage strategy was proposed to improve the efficiency of yard operations and horizontal transportation to corporate with quay crane double cycling. The effects of the mixed storage strategy on terminal operations, including truck travel distance, yard crane operations and the number of required trucks, were analyzed. An approach based on cycle-time models, the queuing theory was proposed to evaluate the performances from long-term run. Results show using the mixed storage strategy, the truck travel distance can be decreased and the number of required trucks and yard crane’s operation time can be reduced by 16% and 26% respectively.     

Terminal and yard allocation problem for a container transshipment hub with multiple terminals

This paper presents an integer programming model for the terminal and yard allocation problem in a large container transshipment hub with multiple terminals. The model integrates two decisions: terminal allocation for vessels and yard allocation for transshipment container movements within a terminal as well as between terminals. The objective function aims to minimize the total inter-terminal and intra-terminal handling costs generated by transshipment flows. To solve the problem, we develop a 2-level heuristic algorithm to obtain high quality solutions in an efficient way. Computational experiments show the effectiveness of the proposed approach.     

A combinatorial benders’ cuts algorithm for the quayside operation problem at container terminals

The quayside operation problem is one of the key components in the management system for a container terminal. In this paper, the integrated models proposed in the previous studies to address the quayside operation problem are examined and one of the potential frameworks is identified. A new method called combinatorial benders’ cuts algorithm is developed to solve the berth-level model in the framework. The computational experiment conducted in this research shows that the proposed approach is more efficient than the branch and cut algorithm embedded in CPLEX.     

Tactical berth and yard template design at container transshipment terminals: A column generation based approach

Quay-side berthing congestion is an emerging challenging issue that arises in busy container transshipment terminals and calls for effective management of terminal operations. This paper tackles the berthing congestion problem by introducing a proactive management strategy from the terminal’s perspective that adjusts the calling schedule of feeder vessels in such a way that the quay-side workload distribution in the temporal dimension can be balanced. Such a schedule template design problem is considered simultaneously with another two tactical level decision problems, berth template design (i.e., determining preferred berthing positions for vessels) and yard template design (i.e., allocating storage yard space to transshipment flows). This highly integrated problem is formulated as a set covering model. Heuristic methods based on column generation are developed to obtain near-optimal solutions in an efficient way. Computational experiments on real-world sized test instances demonstrate the efficiency and effectiveness of the proposed approach.     

Spatial,temporal and institutional characteristics of entry strategies in inland container terminals: A comparison between Yangtze River and Rhine River

Recent decades have brought a growing commitment of investors in the (co-)funding and management of inland terminals, particularly container terminals. However, the actors involved, the forms of third-party entry and the emerging partnerships in inland terminals have only been investigated on a fragmented basis in inland port research. To complement existing inland port research on governance, management and spatial development, this paper analyses entry strategies of actors in inland container terminals on the Rhine and Yangtze in terms of their spatial, temporal and institutional characteristics. The unit of analysis in this paper is the inland container terminal, not necessarily the entire inland port (which might have more than one terminal). The entry strategies and the drivers behind these strategies are examined using a conceptual framework focused on five questions, i.e. who, where, when, why and which way. The empirical application is based on a large dataset of all container terminals on the Rhine and Yangtze. Our findings suggest clear differences between the two rivers in terms of the type of operators, the sequence of inland port development and also the major actors shaping the inland terminal landscape. Despite these differences, there is also some level of similarity, including a low presence of international players, the absence of deepsea (landlord) port authorities and observed waves of single acquisition, multiple-site acquisition, and capital entry in the terminals. Government policies, institutional frameworks and the nature of shipping network development are determinants of inland port investment and the entry strategies adopted by relevant actors. The findings contribute to a better understanding of the drivers and contextual environment guiding entry strategies in inland ports and can help policy makers and port operators in inland rivers to assess and benchmark their strategy. The paper adds to existing literature by considering spatiotemporal aspects of terminal ownership and the strategic considerations of and institutional drivers and impediments to the inland terminal strategies of the corresponding actors.     

Reducing truck emissions at container terminals in a low carbon economy: Proposal of a queueing-based bi-objective model for optimizing truck arrival pattern

This study proposes a methodology to optimize truck arrival patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck arrival pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck arrivals can significantly reduce truck emissions, especially at the gate.     

A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling,with consideration of fleet assignment problem

One of the most important airline's products is to determine the aircraft routing and scheduling and fleet assignment. The key input data of this problem is the traffic forecasting and allocation that forecasts traffic on each flight leg. The complexity of this problem is to define the connecting flights when passengers should change the aircraft to reach the final destination. Moreover, as there exists various types of uncertainties during the flights, finding a solution which is able to absorb these uncertainties is invaluable. In this paper, a new robust mixed integer mathematical model for the integrated aircraft routing and scheduling, with consideration of fleet assignment problem is proposed. Then to find good solutions for large-scale problems in a rational amount of time, a heuristic algorithm based on the Simulated Annealing (SA) is introduced. In addition, some examples are randomly generated and the proposed heuristic algorithm is validated by comparing the results with the optimum solutions. The effects of robust vs non-robust solutions are examined, and finally, a hybrid algorithm is generated which results in more effective solution in comparison with SA, and Particle Swarm Optimization (PSO).     

Congestion,port expansion and spatial competition for US container imports

The purpose of this paper is to analyze spatial competition, congestion and flows of container imports into the United States. An intermodal network flow model is developed and used to analyze congestion in the logistics system for container imports. The results indicate that congestion exists at most ports and its consequences are to raise costs at these nodes, and in some cases to divert traffic to other routes. Finally, if each of the ports expanded, the value of marginal capacity would converge to nil, and expansion would reduce congestion costs and waiting times.     

Sailing speed optimization for container ships in a liner shipping network

This paper first calibrates the bunker consumption - sailing speed relation for container ships using historical operating data from a global liner shipping company. It proceeds to investigate the optimal sailing speed of container ships on each leg of each ship route in a liner shipping network while considering transshipment and container routing. This problem is formulated as a mixed-integer nonlinear programming model. In view of the convexity, non-negativity, and univariate properties of the bunker consumption function, an efficient outer-approximation method is proposed to obtain an ε-optimal solution with a predetermined optimality tolerance level ε. The proposed model and algorithm is applied to a real case study for a global liner shipping company.     

Congestion,port expansion and spatial competition for US container imports

The purpose of this paper is to analyze spatial competition, congestion and flows of container imports into the United States. An intermodal network flow model is developed and used to analyze congestion in the logistics system for container imports. The results indicate that congestion exists at most ports and its consequences are to raise costs at these nodes, and in some cases to divert traffic to other routes. Finally, if each of the ports expanded, the value of marginal capacity would converge to nil, and expansion would reduce congestion costs and waiting times.     

Carbon dioxide emissions and inland container transport in Taiwan

The aim of this study is to estimate the carbon dioxide (CO₂) emissions from inland container transport during the time period of 1998-2008 and predicts the trend of these emissions. The analyses show that the CO₂ emission from inland container transport in 1992 reached 1.03 million tonnes, and the figure drastically increased by 89.3% to 1.95 million tonnes in 2008. Using a multiple regression model, gross domestic product (GDP) and oil price are found to be the key drivers for CO₂ emission. The CO₂ mitigation strategies are discussed in the policy suggestions given that Taiwan is warming at twice global average rate.     

Specification for a dynamic vehicle routing and scheduling system

In an e-commerce environment, order fulfilment is driven by customer demands and expectations. A dynamic vehicle routing and scheduling system may be specified which allows e-commerce customers to select their own delivery Time Windows and have these confirmed on-line as they place their order. The methodology is based upon demand forecasting, which leads to the generation of phantom orders and phantom routes. Subsequently, actual orders substitute for phantom orders in an on-line customer order process. The routing and scheduling method includes using both parallel tour-building and parallel insertion algorithms. Customer service levels are confirmed using GPS tracking and tracing, and a feedback loop uses expert systems or artificial intelligence as an input to the demand forecasting data to restart the whole process.     

Comparison of solution approaches for the train load planning problem in seaport terminals

In this paper the train load planning problem arising in a seaport container terminal is considered. This problem consists in determining the optimal assignment of containers to wagon slots in order to maximize the train utilization and, at the same time, to minimize unproductive operations in the terminal. Different solution approaches based on a mathematical programming model are compared. The best solution procedure, satisfactory both in terms of quality of the obtained solutions and for the computational times, is identified through extensive experimental tests. This procedure could be included in a planning tool to be used in real seaport terminals.     

Simultaneous optimization of schedule coordination and cargo allocation for liner container shipping networks

A liner container shipping carrier usually collects immediately-delivered goods that are produced by manufacturers in world factories, and transports the products to worldwide market destination by offering weekly shipping service. In practice, the carrier has to consider extra demurrage cost of containerized cargos incurred from waiting for weekly shipping service at ports. In this paper, we develop a mathematic programming model to maximize the carrier’s profitability by simultaneously optimizing the ship route scheduling and interrelated cargo allocation scheme. The nonlinear optimization model is transformed into an equivalent mixed-integer linear program, and its applicability is demonstrated by a case study.     

A dynamic approach for aircraft assignment and maintenance scheduling by airlines

The problems of assigning planes to flights and of fleet maintenance operations scheduling are considered in this paper. While recent approaches make use of artificial intelligence techniques running on main frame computers to solve combinatorial optimization problems for nominal operations, a dynamic approach is proposed here to face on-line operation conditions. The proposed solution mixes a Dynamic Programming approach (to cope with the fleet assignment problem) and a heuristic technique (to solve the embedded maintenance schedule problem). When applied to a medium charter airline, this approach shows acceptability characteristics for operational staffs, while providing efficient solutions. The proposed solution scheme can be considered as the basis for the development of an on-line decision support system for fleet operations management within airlines.     

A heuristic algorithm for yard truck scheduling and storage allocation problems

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.     

A strategic network choice model for global container flows: specification, estimation and application

Container flows have been booming for decades. Expectations for the 21st century are less certain due to changes in climate and energy policy, increasing congestion and increased mobility of production factors. This paper presents a strategic model for the movement of containers on a global scale in order to analyse possible shifts in future container transport demand and the impacts of transport policies thereon. The model predicts yearly container flows over the world’s shipping routes and passing through 437 container ports around the world, based on trade information to and from all countries, taking into account more than 800 maritime container liner services. The model includes import, export and transhipment flows of containers at ports, as well as hinterland flows. The model was calibrated against observed data and is able to reproduce port throughput statistics rather accurately. The paper also introduces a scenario analysis to understand the impact of future, uncertain developments in container flows on port throughput. The scenarios include the effects of slow steaming, an increase in land based shipping costs and an increased use of large scale infrastructures such as the Trans-Siberian rail line and the opening of Arctic shipping routes. These scenarios provide an indication of the uncertainty on the expected port throughputs, with a particular focus on the port of Rotterdam in the Netherlands.