Jing-Xin Dong

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.

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.

Optimal container dispatching policy and its structure in a shuttle service with finite capacity and random demands

This paper considers the container-dispatching problem including laden container distributing and empty container repositioning in a two-terminal shuttle service with finite shipping capacity and random customer demands. Unmet demands within one period due to unavailable shipping capacity or insufficient empty containers will be lost based on the assumption that customers have limited patience and the fact that container shipping is a highly competitive sector. The objective is to seek effective container dispatching policies by minimising the total costs incurred by container inventory, container repositioning and lost sales. The optimal dispatching policy is derived by applying the Markov decision process theory. The structural characteristics of the optimal policy are investigated through numerical examples. Based on these structural properties, a four-parameter threshold policy is constructed. A range of numerical examples demonstrates that the proposed threshold policy performs extremely close to or indeed the same as the optimal policy. More importantly, the proposed policy has an explicit form, which is easy-to-understand and easy-to-operate from the managerial and operational perspectives.

Lease term optimisation in container shipping systems

This paper formulates the container leasing problem as part of a dynamic system with multiple voyages and inland transportation times. The purpose is to optimise the length of container lease terms at individual ports on the service route by considering interacting factors such as owned container fleet size, empty container repositioning, inland transportation time, and the associated costs including empty container inventory-holding costs, port lifting-on/off costs, sea transportation costs, inland transportation costs, time-based leasing-in costs, one-off leasing-off costs, and lost demand penalty costs. The problem is tackled at the individual container level. A simulation-based optimisation approach is used to solve the problem under typical container operational rules. Case studies are given to illustrate the application of the model, to compare different lease term selection policies, and to evaluate the impacts of various key factors on lease term decisions.

Assessment of empty container repositioning policies in maritime transport

Purpose – Empty container repositioning is an important issue in the liner shipping industry. Generally stated, two groups of mathematical models have been proposed to tackle this issue. The first group aims to derive time‐dependent origin‐destination matrices that specify the number of empty containers to be repositioned at a decision epoch; the second group aims to develop effective state‐feedback control policies consisting of dynamic decision‐making rules. There is, however, a lack of research into the comparison of these two groups, especially with regard to realistic cases subject to uncertainties. The purpose of this paper is to evaluate and compare the performances of some typical repositioning policies from these two groups and to shed light on their relative merits and suitability in various realistic scenarios.Design/methodology/approach – Based on a literature review, the paper classifies the current empty container repositioning policies into two categories: origin‐destination (OD) based solu...

Multi-criteria evaluation of real-time key performance indicators of supply chain with consideration of big data architecture

Abstract One of the major issues a designer of Big Data Architecture has to trade with is incorporating real-time predictive analytics capability using offline synergistic approaches like simulation, fuzzy analytic network process, and Technique for Order Preference. Further, under this setting, which involves re-engineering of operational units, the present study proposes a simple, yet practical heuristic to quickly handle the unstructured relational key-performance-indicators (KPIs) data of a supply chain that are obtained from the results of the simulation. Within the big data framework, the proposed model can be used as a decision support tool by the companies to evaluate their KPIs in a real-time dynamic system.

The signaling game model under asymmetric fairness-concern information

Under the wholesale price contract, we analyze the influence of the retailer’s fairness-concern information on the wholesale price, order quantity, the profit of each party and the supply chain in symmetry information (SI) condition and asymmetry information (AI) condition respectively. Then, we compute the value of retailer’s fairness-concern information to supplier, and we prove that the profit of all members and supply chain is decreasing with retailer’s fairness concern and the profit in SI condition is always higher than that in the AI condition. Then, we set the signaling game model to reveal the transmission mechanism of retailer’s fairness-concern information, and we analyze the potential separating equilibrium and pooling equilibrium existing in signaling model under asymmetric fairness-concern information. We prove that only when the signal transmission cost is different between retailers with different fairness-concern degree, the signaling model can effectively reveal the role and type of retailers. Finally, we provide some suggestions improve fairness-concern information transmission and optimize supply chain operation by discussing the condition of each separating equilibrium results.