In recent years, the stability of supply chains has been undermined due to many disruptions. Although it is normal for the disruptions in supply chains to occur periodically, they have great impact on the rise of the costs and they create strong imbalances in business. For years, most world trade has been performed by maritime transport due its cost-effectiveness. The COVID-19 pandemic has disrupted the global supply chain like nothing before, and the Russian invasion of Ukraine has only deepened the crisis that is affecting the global supply chain. The focus of this paper has been placed on volatile freight rates in the maritime container industry due to the COVID-19 pandemic and the Russian invasion of Ukraine and the consequences of these crises on the changes of the prices of consumer goods in the European Union.

Inland terminals are becoming an increasingly important factor for disburdening port storage capacities and the expansion of the port gravitational areas. The above defines inland terminals as facilities with prolonged activities of seaports, or an integral part of the port. Due to increased interest in the development of inland terminals, the literature in the field of inland terminals since the beginning of its research (1980) to the latest research in 2015 has been analysedand revised. The review will summarize the literature related to development, classification, technological processes and location of inland terminals. In the end, the paper identifies a new proposition for further research based on the current trends and developments in inland terminals as an important factor of intermodal transport.

Research related to performance evaluation implicates defining work efficiency as result of substituting classic RF by pick by voice technology in warehouse infrastructure. The research outlined the benefits and effect of implementation...

The development of inland terminals helps seaports mitigate inevitable storage capacity problems, extending their gravitational field and strengthening their competitive advantage. Optimizing the container storage, efficiency, and productivity of seaports and inland terminals is becoming increasingly important. The present paper develops a network-based mathematical model to optimize the location assignment of inbound containers at inland terminals. The model’s assumptions are based on the analysis of criteria at representative European inland terminals, and the model aims to reduce unproductive manipulations. The present study is one of the few to develop a single model that integrates all important criteria for container location assignment, including a container’s dimensions, its occupancy, cargo type, the container’s owner, and distance to the final user. These criteria are important for the terminal operator so that they can determine container locations in a way that minimizes unproductive manipulations. Data from a single inland terminal were used to validate the model within the FlexSim CT simulation environment. Our results suggest that the model can reduce unproductive manipulations and associated costs at inland terminals.

The development of artificial intelligence (AI) is profoundly transforming modern supply chains, particularly cold chains in dairy, pharmaceutical and perishable goods industries. By leveraging technologies such as the Internet of Things (IoT), blockchain and predictive maintenance, logistics operations can achieve greater efficiency, quality and sustainability. The dairy sector, with its stringent temperature controls and rapid delivery requirements, is especially well-suited for AI integration. Simultaneously, growing environmental awareness is accelerating the adoption of AI in reverse logistics to support the transition to a circular economy. In this study, we examine the technological foundations and baseline capabilities of AI in logistics, explore how AI supports sustainability-driven reverse logistics and assess its potential to enable the integrated management of cold and general supply chains. To that end, we applied a systematic literature review methodology involving structured database searches, screening and analysis of 95 scientific articles published between 2010 and 2024. The articles were categorised into three domains: AI in logistics, AI in reverse logistics and the integrated management of cold and general supply chains. The findings highlight the need for further research to develop AI-based solutions for predictive maintenance, temperature monitoring, demand forecasting and return management. Such advancements aim to improve the resilience and efficiency of cold chain and reverse logistics systems while enabling integrated, sustainable supply chain management.

The paper discusses the issue of unproductivity during the implementation of operations in inland container terminals. The authors hypothesize that the two main factors influencing the number of unproductive manipulations are the adopted operating strategy and the occupancy level of the storage yard. The presented model classifies the operation time and the waiting time for container handling separately, and also compares the impact of the terminal storage occupancy and selected strategies on the handling time. Based on the collected data, the impact of the number of occupied storage places and the frequency of repetition of operations on the average time of handling a freight unit are simulated. It is noticed that increasing the occupancy of the terminal area above 35% results in a significant increase in the frequency of repetition of operations. In the case of terminal area occupancy of about 50%, the average waiting time for service and the service of a freight unit itself may vary significantly, depending on the adopted strategies for the implementation of operations.