Dong-Ping Song

On cost-efficiency of the global container shipping network

This paper presents a simple formulation in the form of a pipe network for modelling the global container-shipping network. The cost-efficiency and movement-patterns of the current container-shipping network have been investigated using heuristic methods. The model is able to reproduce the overall incomes, costs, and container movement patterns for the industry as well as for the individual shipping lines and ports. It was found that the cost of repositioning empties is 27% of the total world fleet running cost and that overcapacity continues to be a problem. The model is computationally efficient. Implemented in the Java language, it takes one minute to run a full-scale network on a Pentium IV computer.

Empty container repositioning in liner shipping1

The efficient and effective management of empty containers is an important problem in the shipping industry. Not only does it have an economic effect, but it also has an environmental and sustainability impact, since the reduction of empty container movements will reduce fuel consumption and reduce congestion and emissions. The purposes of this paper are: to identify critical factors that affect empty container movements; to quantify the scale of empty container repositioning in major shipping routes; and to evaluate and contrast different strategies that shipping lines, and container operators, could adopt to reduce their empty container repositioning costs. The critical factors that affect empty container repositioning are identified through a review of the literature and observations of industrial practice. Taking three major routes (Trans-Pacific, Trans-Atlantic, Europe–Asia) as examples, with the assumption that trade demands could be balanced among the whole network regardless the identities of individual shipping lines, the most optimistic estimation of empty container movements can be calculated. This quantifies the scale of the empty repositioning problem. Depending on whether shipping lines are coordinating the container flows over different routes and whether they are willing to share container fleets, four strategies for empty container repositioning are presented. Mathematical programming is then applied to evaluate and contrast the performance of these strategies in three major routes. 1A preliminary version was presented in IAME Annual Conference at Dalian, China, 2–4 April 2008.

Characterizing optimal empty container reposition policy in periodic-review shuttle service systems

This paper considers a periodic-review shuttle service system with random customer demands and finite reposition capacity. The objective is to find the optimal stationary policy of empty container reposition by minimizing the sum of container leasing cost, inventory cost and reposition cost. Using Markov decision process approach, the structures of the optimal stationary policies for both expected discounted cost and long-run average cost are completely characterized. Monotonic and asymptotic behaviours of the optimal policy are established. By taking advantage of special structure of the optimal policy, the stationary distribution of the system states is obtained, which is then used to compute interesting steady-state performance measures and implement the optimal policy. Numerical examples are given to demonstrate the results.

Product due date assignment for complex assemblies

A method is described to assign product due dates for multistage assemblies with uncertain manufacturing and assembly process times. Earliest start times of operations are specified by a predetermined production plan and processing time distributions for operations are truncated at minimum processing times. The method systematically decomposes the complex product structures of multistage assemblies into two-stage subsystems. Both exact and approximate distributions of completion time for two-stage assemblies are developed. The latter is applied recursively to multistage assemblies to yield an approximate distribution of product completion time. Product due dates are assigned to either minimise earliness and tardiness costs or to meet a service target. This method is applied to examples which use manufacturing and assembly data from a capital goods company. The results are verified by simulation.

Optimal empty vehicle repositioning and fleet-sizing for two-depot service systems

This paper considers the problem of determining optimal control policies for empty vehicle repositioning and fleet-sizing in a two-depot service system with uncertainties in loaded vehicle arrival at depots and repositioning times for empty vehicles in the fleet. The objective is to minimise the sum of the costs incurred by vehicle maintenance, empty vehicle repositioning and vehicle leasing. A novel integrated model is presented. The optimal empty repositioning policy for a particular fleet size is shown to be of the threshold control type. The explicit form of the cost function under such threshold controls is obtained. The optimal threshold values and fleet-size are then derived. Numerical examples are given to demonstrate the results.

Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands

This article considers the inventory management problem in a supply chain with uncertain replenishment lead-times and uncertain demands. The optimal integrated inventory management (IIM) policy is developed using stochastic dynamic programming theory. The IIM policy is contrasted with two pull-type vendor-managed inventory policies (VMI-1 and VMI-2) and a traditional retailer-managed inventory policy (RMI). Computational results show that in such stochastic supply chains, IIM performs about 23, 15, and 3% better than the optimised RMI, VMI-1 and VMI-2 policies, respectively, while two VMI policies are about 8 and 20% better than the best RMI. The basestock-based VMI-2 is a very good form of VMI. The ANOVA analysis reveals that the replenishment lead-times have the largest effect on the relative performance between IIM and other policies. Numerical examples demonstrated that the IIM policy has good structural properties and can be characterised by a set of switching curves.

Integrated inventory management and supplier base reduction in a supply chain with multiple uncertainties

This paper considers a manufacturing supply chain with multiple suppliers in the presence of multiple uncertainties such as uncertain material supplies, stochastic production times, and random customer demands. The system is subject to supply and production capacity constraints. We formulate the integrated inventory management policy for raw material procurement and production control using the stochastic dynamic programming approach. We then investigate the supplier base reduction strategies and the supplier differentiation issue under the integrated inventory management policy. The qualitative relationships between the supplier base size, the supplier capabilities and the total expected cost are established. Insights into differentiating the procurement decisions to different suppliers are provided. The model further enables us to quantitatively achieve the trade-off between the supplier base reduction and the supplier capability improvement, and quantify the supplier differentiation in terms of procurement decisions. Numerical examples are given to illustrate the results.

A Fluid Flow Model for Empty Container Repositioning Policy with a Single Port and Stochastic Demand

This paper is concerned with an optimal policy for empty container repositions. A single port is considered. The demand is modeled as a two-state Markov chain. The objective is to transport in and out containers so as to minimize the discounted holding, leasing, and repositioning costs. In this paper, the flow of containers is treated as though it is a continuous fluid. Dynamic programming is used to solve the optimal control problem. The associated HJB equations are used to characterize the value functions. The optimal policies are given in terms of threshold levels. Closed-form solutions of these threshold levels are obtained. Sufficient conditions are given in the form of a verification theorem. Numerical examples are reported to demonstrate the results.

Empty Container Repositioning

Empty container repositioning (ECR) is one of the most important issues in the liner shipping industry. Not only does it have an economic effect on the stakeholders in the container transport chain, but it also has an environmental and sustainability impact on the society since the reduction of empty container movements will reduce fuel consumption, and reduce congestion and emissions. This chapter first analyzes the main reasons that cause empty container repositioning. Secondly, we provide a literature review with the emphasis on modeling the ECR problem from the network scope, e.g. modeling ECR in seaborne transportation network, modeling ECR in inland or intermodal transportation network, and treating ECR as a sub-problem or a constraint under other decision-making problems. Thirdly, we discuss the solutions to the ECR problems from the logistics channel scope perspective, which are categorized into four groups including organizational solutions, intra-channel solutions, inter-channel solutions, and technological innovations. Fourthly, we discuss the solutions to the ECR problems from the modeling technique perspective, which includes two broad research streams: network flow models and inventory control-based models. We then present two specific models representing the above two research streams, which aim to tackle the ECR problems in stochastic dynamic environments considering both laden and empty container management.

Quantifying the impact of inland transport times on container fleet sizing in liner shipping services with uncertainties

Container fleet sizing is a key issue in liner shipping industry. Although container shipping is an intermodal transport system, inland container movements are often beyond the control of shipping lines. It is vital to understand how the inland transport times and their variability affect the container fleet sizing. This paper first formulates the container fleet sizing problem in liner services with uncertain customer demands and stochastic inland transport times. Simulation-based optimisation approaches are then employed to solve the problem. Two typical shipping services, one cyclic route in trans-Pacific lane and the other more complicated route in Europe–Asia lane, are used as case studies. A quantitative relationship between the optimal container fleet size and the inland transport time is established. The impact of uncertainties in inland times on the fleet sizing is also investigated. The results provide shipping companies useful insights into making strategic decisions.