In this paper we examine the performance of a quantum annealer on a single product Maritime Inventory Routing Problem (MIRP) with many-to-many route structure, hard inventory constraints, and end-of-horizon considerations. In today’s competitive market, mathematical optimization is becoming an increasingly popular tool to consider for planning a variety of logistics operations across the industry. MIRPs are a class of mathematical optimization problems with the aim to plan efficient sea trade. The task at hand is to optimize the distribution of a bulk product among supplying and demanding ports with limited inventories by a fleet of heterogeneous vessels. A literature review about problem and modelling variations as well as solution methods is provided.
Our considered MIRP variant is well-studied and stands out due to its generality, making it a good candidate to apply and conform to a variety of industry needs. However, one challenge of such models can come by the assumption of a finite planning horizon, penalizing any operations near its end. In order to mitigate such end-of-horizon effects and make the model more realistic, we propose a reward for non-empty vessel inventories at the end of the planning horizon.
With that we avoid the risk of inducing infeasilities, unlike previously applied methods in the MIRP literature.

The main aim of this work is to investigate the capabilities and limitations of Quantum annealing as a new solution method for MIRPs. Previously, this technology has only been considered on simpler problems like the capacitated vehicle routing problem. To this end, we generate a set of test instances, formalized as mixed-integer linear models, and benchmark them on both D-Wave’s quantum annealer and a laptop with CPLEX, while varying the computation time.
As one of the main takeaways, we find that on the linear test instances the annealer does not profit from longer computation times.

In this paper, we assess whether the impacts of the stricter 2015 Sulfur Oxides (SOx) regulation within the Sulphur Emission Control Area (SECA) influenced shipowners' strategies in SECA ports. This SOx level is currently the standard applied in all SECAs. This research is essential because there has been limited validation of assumptions in SECA literature. Indeed, SECAs are primarily assessed from the perspective of pollution reduction and benefits on human health (Zheng et al., 2019; Zhu et al., 2021; Wan et al., 2019; Zhang et al., 2020, 2022; Viana et al., 2015), but very few studies have evaluated the ex-post impacts of SECAs from the perspectives of shipowners or ports' outcomes (Fan et al., 2023; Chang et al., 2018).

The policy of interest was introduced in 2015 and applied to all SECA ports. We constructed our dataset from 2012 to 2019 and chose the Northern European ports for our analysis. Using a difference-in-differences model, our main contribution is to assess the impacts of SECAs on calling patterns at SECA ports, as well as on ship characteristics and the contract strategies employed by shipowners. In our identification strategy, we selected two groups of ports: the European Northern Sea ports, which were treated with the SECA policy in 2015, and the European Mediterranean Sea ports, which were the non-treated group. We trace the routings, vessel characteristics (capacity, age, compliance option) and contracts of vessels for all containerships calling at these 172 ports. Building this database provided us with more than 2 million lines of data.

The significant expected contribution is to answer and test the predominant body of SECA literature that focuses on optimizing shipowners' compliance strategies by providing ex-post results. We expect differentiated results depending on whether the route connects with another SECA or not, as well as potential differentiated effects depending on the size of the vessel and the compliance option chosen by the shipowners. Additionally, results may vary based on the specific companies involved and the contracts associated with the ship. These results will be valuable for addressing part of the academic literature and informing policymakers. Notably, substantial policy implications are expected in the phase of new ECAs being discussed for potential Atlantic and Korean SECAs. Additionally, there are more concrete proposals already on the Marine Environment Protection Committee agenda for the Norwegian and Canadian Arctic SECAs, and the introduction of the Mediterranean SECA is expected soon. This is particularly significant since the SOx level that will be applied is the same as the one reduced in the 2015 reform.

Events such as pandemics, natural disasters, and even terrorist attacks have increased the emphasis on mitigating disturbances and disruptions in supply chains, stimulating research on Supply Chain Resilience (SCR). However, the concept of resilience and how supply chains can become resilient remains unclear, making measuring resilience difficult. The literature presents multiple definitions of SCR, but in summary, SCR is described as the ability of a supply chain to anticipate, withstand, and recover from disruptions while maintaining operations and delivering products and services.

Concurrently, a new challenge has arisen with the emergence of digital technologies: a massive influx of unstructured data. Through advanced analytics techniques, Big Data Analytics (BDA) can analyze large and unstructured datasets to extract valuable insights and uncover hidden patterns, correlations, and trends that can guide decision-making, generate business value, and enhance supply chain operations. BDA enhances supply chains by increasing their visibility, analytical capabilities, flexibility, responsiveness, and reliability and improving their ability to adapt to external changes rapidly. By enabling supply chains to recover when disrupted, BDA increases its risk resilience capacity. These benefits highlight the importance of developing BDA capabilities and IT infrastructure to ensure better coordination. Although BDA has proven effective in helping supply chains resist disruptions and increase resilience, there remains a gap in understanding how SCR and BDA intersect and can be effectively leveraged together.

Through an initial literature review, research opportunities were identified. While studies have shown BDA's potential in improving SCR, the specific mechanisms and most effective BDA capabilities to do so remain poorly understood (Hasan, et al., 2024). Additionally, there is a limited exploration of the interaction between BDA capabilities and SCR, especially regarding the best configurations, challenges and barriers to BDA adoption and implementation in supply chains (Jiang, et al., 2023). Some authors point out the need to consider the various stages of supply chain resilience: readiness, responsiveness, and recovery (Zamani, et al., 2022).

The proposed research intends, through a systematic literature review, to identify the most effective BDA capabilities for improving SCR and explore how BDA can improve SCR's key dimensions. Therefore, the study aims to provide valuable insights for organizations seeking to build more resilient and adaptive supply chains. It also intends to lay the groundwork for further investigation into this critical area and to develop comprehensive strategies to enhance SCR through advanced data analytics.

References

Hasan, R. et al., 2024. Critical analysis of the impact of big data analytics on supply chain operations.. Production Planning & Control, 35(1), pp. 46-70.

Jiang, Y., Feng, T. & Huang, Y., 2023. Antecedent configurations toward supply chain resilience: The joint impact of supply chain integration and big data analytics capability. Journal of Operations Management, Volume Volume 70.

Zamani, E. D., Smyth, C., Gupta, S. & Dennehy, D., 2022. Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review.. Annals of Operations Research, Volume Volume 327, p. 605–632.