Manufacturing companies who ship goods globally often rely on external Logistics Service Providers (LSPs) to manage the containerization and transportation of their freight. Those LSPs are usually required to follow rules when deciding how to mix the goods in the containers, which complicates the planning task. In this paper, we study such a freight containerization problem with a specific type of cargo mixing requirements recurrently faced by an international LSP. We show that this problem can be formulated as a Multi-Class Constrained Variable Size Bin Packing Problem: given a set of items that all have a size and a fixed number of classes for which they can take certain values, the objective is to pack the items in a minimum-cost set of bins while ensuring that the size capacity and maximum number of distinct values per class are not exceeded in any of the bins. We propose two adapted and one novel greedy heuristics, as well as an Adaptive Large Neighborhood Search (ALNS) metaheuristic, to find feasible solutions to the problem. We also provide a pattern-based formulation that is used to obtain lower bounds using a Column Generation approach. Using three extensive datasets, including a novel one with up to 1000 items and 5 classes reflecting real industrial cases, we show that the novel greedy heuristic outperforms the adaptations of the existing ones and that our ALNS yields significantly better solutions than a commercial solver within a mandatory 5-minute time limit. Practical insights are given about the solutions for the industrial benchmark.
This paper describes the challenges of the maritime supply chain compared to land transport and discusses the new digital initiatives to simplify the processes and enable a better plan for the entire supply chain. First, the background is outlined with an example of the extensive admin processes in maritime transport compared to road transport, followed by a case example presenting the processes of a booking. The case study concludes that the lack of integration is costly in terms of both admin resources, as well as lost capacity on some ships and missing capacity on others. Finally, the evolution of new digital initiatives are discussed, both in general and in terms of competing “alliances” as seen in the airline industry. The paper concludes that the information exchange in the maritime industry has moved drastically in the last 3 years and that one initiative, TradeLens, seems to have gained a position as maritime standard despite a problematic start with many competing initiatives.
Supply chain researchers are confronted with a dizzying array of research questions, many of which are not mutually independent. This research was motivated by the need to map the landscape of research themes, identify potential overlapping areas and interactions, and provide guidelines on areas of focus for researchers to pursue. We conducted a three-phase research study, beginning with an open-ended collection of opinions on research themes collected from 102 supply chain management (SCM) researchers, followed by an evaluation of a consolidated list of themes by 141 SCM researchers. These results were then reviewed by 10 SCM scholars. Potential interactions and areas of overlap were identified, classified, and integrated into a compelling set of ideas for future research in the field of SCM. We believe these ideas provide a forward-looking view on those themes that will become important, as well as those that researchers believe should be focused on. While areas of research deemed to become most important include big data and analytics, the most under-researched areas include efforts that target the “people dimension” of SCM, ethical issues and internal integration. The themes are discussed in the context of current developments that the authors believe will provide a valuable foundation for future research.
Ship recycling refers to the process of dismantling vessels with the purpose of extracting and recovering materials for reuse, particularly the steel. The aim of this paper is to map the supply chain of ship recycling. This exploratory and qualitative research provides a glimpse on how regulations influence the supply chain management through inter-organizational arrangements. It considers the trade-offs and combinations of financial and sustainable values that, in many ways, determine these inter-organizational arrangements. Preliminary findings show that there are conflicts of interest with the ship recycling stakeholders. Although compliance of regulations should foster better transparency in the supply chain, these regulations have not yet fully embraced social aspects, such as the fact that domestic demand and supply for steel, as well as many jobs, are dependent on this industry. On the contrary, the initiatives to regulate ship recycling might induce negative effects. This paper suggests that transaction costs analysis and the principal agency theory are two complementary theories for analyzing inter-organizational relationships in the supply chain of ship recycling.
The report is organized as follows. The introduction will lay out the current state-of-play of eco-efficiency and the zeitgeist of the current situation on maritime that we find ourselves in, in 2020. The next section will provide some historical context looking back to 2010 and 2000 to trace the trajectory and developmental course on which we are. The core contribution of this report is the Maritime Operations Roadmap that can be found in Figure 1 on page 9. This illustration plots the expectations for technological capabilities and policy from 2020 to 2030.
Having the right spare part at the right time to the right place for ship maintenance to the minimal possible costs is an exigent management problem that maritime shipping companies face. This is especially challenging in bulk shipping where routes are not fixed, but subsequent port calls depend on spot market dynamics. Thus, spare parts allocation ahead in time is limited, but possible if failures rates of ship components and their timing can be foreseen, so that spare parts can be allocated to hedge against the risk of long waiting times and thus ship downtimes. Thus, monitoring the condition of components key to the ships performance is essential to the task. This can enable companies to significantly reduce operational costs of their fleet leading to a competitive advantage in a highly volatile market regarding demand and demand-driven freight rates.
However, shipping companies seem far away from applying such methods due to various challenges ranging from data gathering and cultivating an understanding of data quality needs, adaptation to move from preventive towards predictive and condition-based monitoring, and the introduction and application of decision support tools for sourcing, spare parts allocation, and inventory management.
In this paper, we investigate the current state of the art of maintenance and related spare parts logistics management for maritime shipping and discuss the application of methods to the bulk carriage market. We add practical knowledge from case companies and discuss how challenges can be overcome in providing guidelines for companies.
An increasing number of disruptions in ports, plants and warehouses have generated ripple effects over supply networks impacting economic activity. We demonstrate how the spread of the pandemic geographically expands the ripple effect by reducing the workers' participation in production, so undermining the ability of firms and, as a result, the entire cross-border sup- ply chain network to satisfy customers' demands. Our model of the spatio-temporal dynamics of the propagation of Covid-19 infection for supply networks contributes toward ripple effect visualisation and quantification by combining the flow of goods and materials through a typical global supply chain with an epidemiological model. The model enables prospective analyses to be performed in what-if scenarios to simulate the impact on the workforce in each node. The outcome should be helpful tools for managers and scholars. Results from this research will help mitigate the impact and spread of a pandemic in a particular region and the ability of a supply network to overcome the ripple effect. A stylised case study of a cross-border supply chain illustrates the ripple effect by showing how waves with crests at varying dates impact the ability to serve demand showing how a supply chain manager can obtain a forward-looking picture.
Purpose
The purpose of this paper is to investigate the impact of cloud computing (CC) on supply chain management (SCM).
Design/methodology/approach
The paper is conceptual and based on a literature review and conceptual analysis.
Findings
Today, digital technology is the primary enabler of supply chain (SC) competitiveness. CC capabilities support competitive SC challenges through structural flexibility and responsiveness. An Internet platform based on CC and a digital ecosystem can serve as “information cross-docking” between SC stakeholders. In this way, the SC model is transformed from a traditional, linear model to a platform model with the simultaneous cooperation of all partners. Platform-based SCs will be a milestone in the evolution of SCM – here conceptualised as Supply Chain 3.0.
Research limitations/implications
Currently, SCs managed holistically in cyberspace are rare in practice, and therefore empirical evidence on how digital technologies impact SC competitiveness is required in future research.
Practical implications
This research generates insights that can help managers understand and develop the next generation of SCM with the use of CC, a modern and commonly available Information and Communication Technologies (ICT) tool.
Originality/value
The paper presents a conceptual basis of how CC enables structural flexibility of SCs through easy, real-time resource and capacity reconfiguration. CC not only reduces cost and increases flexibility but also offers an effective solution for disruptive new business models with the potential to revolutionise current SCM thinking.
This paper studies the design of a mid-scale maritime supply chain for distribution of liquefied natural gas (LNG) from overseas sourcing locations, via a storage located at the coast, before transporting the LNG on land to industrial customers. The case company has signed contracts with a number of initial customers and expect that there will be more customers and increased demand in the years to come. However, it is currently uncertain whether and when new contracts will be signed. To capture this uncertainty with regard to which and how many future customers there will be, which directly affects the demand, we propose a multi-stage stochastic programming model, which maximizes the expected profits of the supply chain. The model aims at aiding decisions concerning the import of LNG, investments in floating storage units and customer distribution systems, and it has been applied on a real case study for distributing LNG to customers in a Brazilian state. It is shown that explicitly considering uncertainty in the modeling of this problem is very important, with a Value of Stochastic Solution of 13.2%, and that there are significant economies of scale in this supply chain. Most importantly, the multi-stage stochastic programming model and the analysis presented in this paper provided valuable decision support and managerial insights for the case company in its process of setting up the LNG supply chain.
Sustainable biofuel supply chain is a key to sustainable manufacturing and the future of production. Greener production is now becoming an order qualifier for the global competition. Modeling biofuel supply chains that achieve economic, social, and environmental feasibility is a challenge. This article develops biofuel platform planning and optimization that unifies biofuel product, production process and networks design into an umbrella of sustainable supply chain planning. A design of biofuel supply chain networks under various production paths is considered. The modeling results show that an optimum region of composition ratio between rice straws and waste cooking oils can be set within the range from 0% to 50%. Bio-diesel is favored over ethanol by occupying over 40% of the total biofuel outputs. However, ethanol yield is 99.1% and therefore it is sufficient to be directly mixed with gasoline at final depots. In terms of social contribution, it is estimated that the supply chain contribution to the case country GDP is about 0.17%. Looking at the above statistics, future research on global economic impacts and competitiveness of biofuel production is suggested.