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.     

Optimal space for storage yard considering yard inventory forecasts and terminal performance

This paper presents a method for forecasting the yard inventory of container terminals over an extended period, and addresses an integrated yard planning problem for determining the optimal storage space utilization by considering the yard congestion effect on terminal performance. A formulation based on random variables and probabilistic functions was developed, which allows prediction of the storage space requirement without requiring fully-integrated simulation models. Then, an integrated cost objective function was defined. Numerical experiments were performed to illustrate how the forecasting model works and to support decision-making on yard planning and design for both inbound and outbound/transshipment areas.     

Container yard template planning under uncertain maritime market

A yard template determines the assignment of spaces in a yard for arriving vessels. Fluctuation of demand for freight transportation brings new challenges for making a robust yard template when facing uncertain maritime market. A model is proposed for yard template planning considering random numbers of containers that will be loaded onto vessels that visit the port periodically. Traffic congestions and multiple schedule cycle times for vessel arrival patterns are also considered. Moreover, a meta-heuristic method is developed for solving the model in large-scale cases. Numerical experiments are conducted to validate effectiveness and efficiency of the model.     

Joint planning of berth and yard allocation in transshipment terminals using multi-cluster stacking strategy

In this work, a joint planning problem for berth and yard allocation in transshipment terminals is addressed. Multi-cluster stacking strategy is proposed to split each transshipment flow into a number of container clusters and then stack each cluster in different yard blocks. A mixed integer quadratic programming model is formulated to minimize the total distance of exchanging containers between mother vessels and feeders, and the workload imbalance among yard blocks. A novel three-stage heuristic solution approach is developed and extensive numerical experiments are conducted to show the effectiveness of the proposed approach and the benefit of the multi-cluster strategy.     

The application of inventory transshipment modeling to air cargo revenue management

This paper applies an inventory transshipment modeling approach to investigate the air cargo revenue management problem for an airline operating in a two-segment network. Building upon an extension of the classic two-location inventory transshipment model, we develop a framework to optimize an airline’s cargo overbooking decisions in a two-segment network setting. We find consistent evidence indicating that network-based global optimization always leads to greater expected profits than does local (i.e., market by market) optimization. Further, the magnitude of profit improvement is found to be most significant when local shipments have a relatively higher freight yield compared to flow-through shipments. Finally, our results indicate that global optimization contributes to greater profit improvement as offloading penalty costs become higher.     

Container storage and transshipment marine terminals

This study addresses the storage arrangement of transshipment containers on a container yard, in order to carry out efficiently the ship handling operations at a terminal where mega-containerships call. An optimization model is specified to investigate the flow of containers from the mega-containership to feeder ships using intermediate storage at the yard. A heuristic based on the lagrangian relaxation is formulated. The quality of the heuristic approach is tested in a number of experiments. In the experiments, various situations are analyzed with respect to mega-containership arrival rates, some strategies for stack arrangements and terminal layouts.     

Determining fixed crane areas in rail–rail transshipment yards

To enable rapid container transshipment between freight trains in modern rail–rail transshipment yards efficient computerized scheduling procedures are indispensable. This paper proposes a dynamic programming approach, which determines yard areas for gantry cranes, so that the workload is evenly spread among cranes and, thus, train processing is accelerated. In a straightforward simulation of transshipment yard operations, the effect of optimal crane areas vs. equally sized areas is studied, the latter being a common real-world policy. The results indicate a remarkable speed-up of train processing if optimal crane areas are applied.     

Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion

The current literature in the rail–truck intermodal transportation of hazardous materials (hazmat) domain ignores congestion at intermodal yards. We attempt to close that gap by proposing a bi-objective optimization framework for managing hazmat freight that not only considers congestion at intermodal yards, but also determines the appropriate equipment capacity. The proposed framework, i.e., a non-linear MIP and a multi-objective genetic algorithm based solution methodology, is applied to a realistic size problem instance from existing literature. Our analysis indicates that terminal congestion risk is a significant portion of the network risk; and, that policies and tools involving number of cranes, shorter maximum waiting times, and tighter delivery times could have a positive bearing on risk.     

Port multi-service congestion

Port multi-service congestion occurs when port users of two or more different services (i.e., multi-services) provided at the same port node or over the same port link interfere with one another to the extent that they experience service congestion at the shared node or over the shared link. Container port nodes shared in the provision of port multi-services include, for example, the berth and yard. Container port links shared in the provision of port multi-services include, for example, the yard-to-departure-gate link, entrance-gate-to-yard link, berth-to-yard link and yard-to-berth link. If port multi-service congestion exists at a port node (or over a port link), then port multi-service congestion can be propagated to other port nodes and links in the port as long as there is a connecting path.     

European intermodal freight transport network: Market structure analysis

The analysis of market structure and concentration measures for the Intermodal Freight Transport (IFT) market is important to avoid market failure and to find the areas for policy making to promote IFT market share. This analysis can be performed for separate segments, for example, the market for transshipment service or the market for main-haulage service. However, due to the multistage characteristic of IFT service, the segmental analysis gives an incomplete view of the IFT market at the network level. In a previous paper (Saeedi et al., 2017), we present the Intermodal Freight Transport Market Structure (IFTMS) model to conduct a network-based study of the IFTMS in which distinctive actors (i.e., pre/post haulage operators, terminals, rail/barge operators, transport chains, and corridors) are competing at different levels inside distinctive markets to deliver an integrated IFT service. There are two main challenges in the application of IFTMS model in real cases, for example, the European IFT network. First, the definition of the geographical and spatial border of the transshipment market areas is needed to determine which actors are potentially competing for a specific service demand. The second challenge is the lack of disaggregated data and the consistency of existing data in nodes (i.e., the transshipment areas) and links (i.e., the rail and barge operators). To cope with these challenges, we develop a four-step methodology in which a model-based approach is used to define the geographic boundaries of the transshipment submarkets and provide detailed and consistent data for market analysis. We also apply the IFTMS model to study the market structure of European intermodal network. Our analysis shows that the majority of transshipment markets as well as main-haulage markets are highly concentrated markets. The corridor markets – which include the IFT chains – are unconcentrated markets. Furthermore, the majority of corridors in the European Union are inside highly concentrated origin-destination markets.     

A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.     

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.     

Robust schedule design for liner shipping services

This paper examines the design of liner ship route schedules that can hedge against the uncertainties in port operations, which include the uncertain wait time due to port congestion and uncertain container handling time. The designed schedule is robust in that uncertainties in port operations and schedule recovery by fast steaming are captured endogenously. This problem is formulated as a mixed-integer nonlinear stochastic programming model. A solution algorithm which incorporates a sample average approximation method, linearization techniques, and a decomposition scheme, is proposed. Extensive numerical experiments demonstrate that the algorithm obtains near-optimal solutions with the stochastic optimality gap less 1.5% within reasonable time.     

Robust schedule design for liner shipping services

This paper examines the design of liner ship route schedules that can hedge against the uncertainties in port operations, which include the uncertain wait time due to port congestion and uncertain container handling time. The designed schedule is robust in that uncertainties in port operations and schedule recovery by fast steaming are captured endogenously. This problem is formulated as a mixed-integer nonlinear stochastic programming model. A solution algorithm which incorporates a sample average approximation method, linearization techniques, and a decomposition scheme, is proposed. Extensive numerical experiments demonstrate that the algorithm obtains near-optimal solutions with the stochastic optimality gap less 1.5% within reasonable time.     

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.     

Assessment of non-recurrent traffic congestion caused by freeway work zones and its statistical analysis with unobserved heterogeneity

Freeway work zones with patching, paving, lane marking, debris removing, and weeding cause temporary capacity reduction in the freeway and may lead to non-recurrent traffic congestion. Such non-recurrent traffic congestion amounts to 10% of total traffic congestion in the U.S. and 31% in Germany. Non-recurrent traffic congestion has been estimated by using the capacity and the number of closed lanes in work zones and the upstream traffic demand of work zones. However, the number of the closed lanes may be insignificant due to operational strategies such as using the shoulder area and composing additional lanes by temporarily reducing the existing lane width to mitigate traffic congestion. Therefore, the objective of this study is to develop a method to quantify non-recurrent traffic congestion caused by freeway work zones based on traffic flow data and spatio-temporal work zone information. In addition, to demonstrate the efficacy of the developed method, a case study is conducted based on one-year historical traffic data and work zone data on major freeways in Korea. Then, multivariate statistical analysis with unobserved heterogeneity is performed to describe factors of non-recurrent traffic congestion caused by work zone activities. Due to the fact that a work zone project is usually implemented according to schedule, such negative impact as non-recurrent traffic congestion is inevitably produced. Thus, the results can be practical for the performance evaluation of congestion management programs for work zone by quantifying non-recurrent traffic congestion. Additionally, the results from the statistical analysis can be potentially useful in developing a forecasting model for providing travelers with traffic information such as an alternative route to escape non-recurrent traffic congestion by freeway work zones.     

The integrated yard truck and yard crane scheduling problem: Benders’ decomposition-based methods

This paper proposes a novel integrated model for yard truck and yard crane scheduling problems for loading operations in container terminal. The problem is formulated as a mixed-integer programming model. Due to the computational intractability, two efficient solution methods, based on Benders’ decomposition, are developed for problem solution; namely, the general Benders’ cut-based method and the combinatorial Benders’ cut-based method. Computational experiments are conducted to evaluate the effectiveness of the proposed solution methods.     

Comparing heuristic algorithms of the planar storage location assignment problem

This paper discusses the newly defined planar storage location assignment problem (PSLAP). We develop a mathematical programming model and GA-based and dynamic PSLAP heuristic algorithms for the solving procedure. Using the testing set, we compare the performance of GA-based and dynamic PSLAP heuristic algorithms. The mathematical programming model is utilized as a comparison criterion. The comparison results demonstrate that the dynamic PSLAP heuristic algorithm performs better than the other solving procedures. In addition, we describe simulation experiments conducted to investigate the effects of stock yard layout and production schedule instability on the operation of the block stock yard.     

The strategic berth template problem

A marine container terminal operator may have a situation with excessive calling requests to be served especially when some new service contracts are under consideration. For this situation, we propose a strategic berth template problem (BTPS) that selects the ships among the requesting ones to be served and arrange their berth-windows within a limited planning horizon. The BTPS employs the subgradient optimization procedure, which is an improved version of the procedure that the authors developed for the operational berth allocation problem. A wide variety of numerical experiments indicate the improved subgradient procedure works well for the BTPS.     

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