The Internet of Things (IoT) can bring radical advancements in the domain of waste collection, as it enables the organization of demand-responsive schedules which leads to higher efficiency operations. One major challenge in the deployment of demand-responsive schedules, nevertheless, is the uncertainty they bring in the planning of resources as they follow the daily waste demand. This is undesirable in real-life operations as it makes it difficult to reserve resources and ensure the stability of operational processes. Therefore, waste collection scheduling approaches need to be devised that are not only demand-responsive but also supply-friendly. In this paper, we present a solution approach for the waste collection vehicle routing problem in an IoT context (IoT-WCVRP) that focuses on these requirements. We demonstrate its applicability through a case study of Rotterdam in The Netherlands, where real-life household waste data are used and the observed waste collection operations in the city are compared against the optimized outcomes of the model. The application results show that our IoTWCVRP approach achieves the stated demand and supply trade-off, increases the vehicle utilization rates by 5%, and reduces emissions and travelled kilometres by 6% and 8% respectively.

Very few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight solutions or policies. Especially the behavioral responses of logistic agents are difficult to include systematically in impact assessments. This is mainly due to limitations on urban freight data and absence of validated and proven simulation tools. We present an urban freight simulator: Multi-Agent Simulation System for Goods Transport (MASS-GT). MASS-GT is an agent-based model consisting of a framework of discrete choice and optimization models to describe the logistic choices of shippers, carriers, producers and consumers. The disaggregate level of detail allows the analysis of a wide variety of logistic developments and policies across all or specific logistic segments. The model was first implemented for a study area in the Netherlands and calibrated and validated using a variety of data sources.

De transitie naar een circulaire economie vraagt om intensieve samenwerking binnen waardeketens. Dit artikel bouwt op concepten voor de analyse van logistieke systemen zoals ge¨ıntroduceerd door prof. Kees Ruijgrok, en verbindt deze aan recent onderzoek naar Value Chain Collaboration en circulaire prestaties. Met behulp van kwalitatieve data, verzameld via semi-gestructureerde interviews, en kwantitatieve data, verkregen uit twee opeenvolgende vragenlijsten, is de relatie tussen samenwerking en prestaties op de Rladder van de circulaire economie nader onderzocht. Samenwerking blijkt sterk te correleren met circulaire prestaties, met name in technologie-intensieve sectoren die profiteren van gedeelde platforms en infrastructuur. Traditionele sectoren lijken te worden belemmerd door een gebrek aan vertrouwen en beperkte middelen. Deze resultaten benadrukken de noodzaak van maatwerkoplossingen om unieke uitdagingen en kansen binnen sectoren te benutten. Het artikel beoogt bij te dragen aan de literatuur over circulaire economie en samenwerking in de logistiek, als basis voor toekomstig onderzoek en praktijktoepassingen

The energy transition is reshaping global trade flows, introducing uncertainty into energy-related liquid bulk logistics, particularly within ports. Despite the significance of liquid bulk in global supply chains, existing port choice models are primarily developed for containerized cargo. This study investigates the key determinants of decision-making in liquid bulk logistics within the context of sustainability transitions. Using a multi-case study approach, including stakeholder interviews and qualitative analysis, we identify factors shaping infrastructure planning, port selection, storage, and transportation modes.

The findings reveal that logistical choices in liquid bulk are highly interdependent, shaped by supply chain structures, stakeholder dynamics, and regulatory frameworks. As ports might evolve into multienergy hubs, new actors and uncertainties emerge, particularly regarding the role of hydrogen and biofuels. Understanding these evolving dynamics is crucial for optimizing logistics strategies and ensuring efficient, sustainable energy supply chains.

Despite the importance of urban freight transportation for the accessibility and livability of cities, few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight transportation solutions or policies. There is a lack of transparent literature on the full specification and estimation of these models, which not only hampers continued research, but also the development of evidence-based urban freight transport policies. We present the urban freight simulator Multi-Agent Simulation System for Goods Transport (MASS-GT) with its full specification and empirical implementation for a study area in The Netherlands. It concerns an agent-based model based on a framework of discrete choice and optimization models, which describes logistic choices of shippers, carriers, producers and consumers. The disaggregate level of detail allows the analysis of a wide variety of logistic developments and policies across all or specific logistic segments. The model is estimated and validated using a variety of data sources: truck trip diaries, supply/use statistics, an e-commerce demand survey, traffic counts and other relevant statistics. The article presents the full specifications of the model and their empirical estimation, including the data sources used. Also, the validity of the model is evaluated using road freight traffic counts. Finally, examples of applications of the model to case studies are provided.

Logistics plays a crucial role in modern society, particularly in densely populated urban areas, facilitating the transportation of goods. Last-mile e-commerce deliveries are emissions-intensive, contributing significantly to CO2 levels and traffic congestion. Addressing this challenge requires systemic changes in last-mile delivery ecosystems. Based on this observation, in alignment with the EU decarbonisation goals, the URBANE project (GA101069782) aims to promote the adoption of sustainable and environmentally friendly last-mile delivery solutions by introducing a collaborative layered “Platform as a Service” (PaaS) paradigm. The initiative focuses on establishing Physical Internet (PI) inspired interventions combined with the implementation of innovative tools, such as agent-based and AI models, employing a Digital Twin platform addressing the operational and strategic planning challenges of city logistics networks. A multi-factorial impact assessment radar further enhances the evaluation of the PI interventions’ effectiveness. The platform fosters collaboration among urban logistics stakeholders governed through “green” smart contracts, addressing security and privacy concerns by using a blockchain infrastructure and digital IDs, creating a trustworthy system for collaboration. The paper showcases the applicability of the URBANE Innovation Transferability Platform in designing, measuring, testing, and validating targeted logistics interventions in Lighthouse Living Labs. Cities and logistic operators receive suggestions for informed data-driven decision-making coupled with integrated and transferable applications that can be standardised and structured, aligned with the targets set in a citie’s Sustainable Urban Logistics Plan (SULP).

The transport sector is the second highest emitting sector in the Netherlands, with 19 % of the total energy consumption. Where other sectors are becoming more sustainable, the transport sector remains one of the most difficult to decarbonize, despite the many studies in this field. This research aims to gather a list of potential measures and combine them to reach an 80% reduction of CO2 emissions in 2040 for the hinterland freight corridor of Rotterdam – Venlo which has a high rail freight intensity. Literature study and expert interviews established a list of potential measures. Using an iterative normative scenario design approach, a list of 8 potential measures with corresponding targets was drafted. After computation, a reduction of 80% is estimated for the corridor. The results show that for this particular corridor, the reduction depends greatly on the availability and adaptability of biodiesels and the electrification of vehicles and vessels. In contrast, measures aiming to improve the logistical
efficiency do reduce the total energy required and could therefore alleviate challenges related to biodiesel availability and electrification, but have a smaller potential in reducing CO2 emissions.

Dry port construction facilitates intermodal freight transport in the import and export corridors, especially for landlocked countries. Selecting the optimal locations for dry ports is a crucial component of national planning. In this study, multi-criteria decision-making (MCDM) combined with GIS was used to map suitable sites for dry ports. Essential criteria for selecting optimum dry port locations were identified from the literature and a Simple Multi-Attribute Ranking Technique (SMART) was used for expert weighting these criteria. The results revealed that distance from road and distance from railway are the two most important criteria, while distance from a seaport is the least important. Application of the method to identify optimal dry port locations in Ethiopia showed that most of its territory is moderately suitable for dry port location. However, most of the existing dry ports in the region are found to lie within the highly suitable areas. Overall, the suitability map developed in this study provides a rich basis of information for future sustainable dry port investments.

Game-theoretic models are frequently used to analyse the effects of information availability and quality on supply chain decision-making. Although information asymmetry plays a vital role in shaping sustainable supply chains, a comprehensive review of these models within this context remains lacking. This study conducts a systematic literature review and performs an in-depth content-based analysis of 73 peer-reviewed journal articles, categorising them based on their assumptions regarding supply chain structure, information structure, and interaction among supply chain members. We find that researchers are extending traditional supply chain models to address emerging challenges and opportunities driven by sustainable practices under asymmetric information. However, the research remains in a preliminary phase, with most models relying on simplified settings – typically dyadic, single-product, and single-period frameworks – and focusing primarily on demand and cost information asymmetries. Multilateral information structures and non-contractual coordination mechanisms remain largely unexplored. Theoretical advancements have considerably outpaced empirical validation, revealing a critical gap in the integration of real-world practices. Our findings highlight the importance of information sharing and coordination mechanisms in achieving sustainability outcomes and improving supply chain performance. These insights enrich the theoretical discourse on information asymmetry in sustainable supply chains.

The e-commerce growth trend has great potential to influence both the nature and the dimension of the challenges policymakers will face in the near future. In this sense, the purchasing habits of the end consumer have undergone a significant change with the development of the emerging information and communication technologies that impact on the purchase behaviour and the way of receiving the item bought. The goal of the paper is thus to analyse cutting-edge last mile delivery alternatives while looking at the characteristics that determine the preferred alternative for receiving e-purchases. The identified new alternatives besides traditional mail are: crowdshipping, delivery to the car trunk, delivery by autonomous delivery robots, unattended parcel locker, attended pick up point and click-and-collect service. The paper presents the methodology for designing and delivering, as well as the findings of a survey carried out for investigating users' behaviour, after reviewing the key attributes and levels that influence end consumers in choosing how to receive their e-purchases.

As ports are experiencing heavier traffic, the pressure to improve port call processes is increasing. Port call optimization (PCO) is one of these improvement initiatives, enabling the arrival of vessels to the port just-in-time when the vessel services, like pilotage, towage, and mooring, are all readily available. Otherwise, vessels that sailed at full speed to arrive at the port may have to wait, idling at anchorage, occupying space, burning fuel, and leading to increased congestion. One of the main challenges in the implementation of PCO is determining the time at which availability of these services can be guaranteed. The paper addresses this challenge by presenting a model that jointly schedules vessels and service providers. It extends the current approaches to allow application to larger and busier ports, where repositioning times for pilots and tugboats is highly variable and vessels experience waiting times between services. The problem is formulated as a mixed-integer linear programming one and is modelled in continuous time. We test alternative scheduling strategies using three different objective functions, based on the current ‘first-come-first-serve’ approach, a minimal level of service, and the best capacity utilization. The model is applied on data made available by the Port of Rotterdam, and it provides a full-service schedule for vessels and service providers.

The demand for new offshore wind farms is increasing at a rapid pace, and the installation rate must be quadrupled by 2030 to meet the ambitions of European countries. The installation of the superstructures involves several components and is highly weather-dependent, making this an important bottleneck. In this paper, we evaluate the two main strategies for the installation of superstructures: feedering and shuttling. With feedering, the installation vessel is fed with components by feeder vessels directly from manufacturing ports. With shuttling, the installation vessel retrieves the components itself from a marshalling port. In contrast to existing studies, we include manufacturing ports and their production rate to have a better understanding of their influence on the installation rate and develop a rolling horizon optimization-simulation framework composed of a mixed integer linear programming model and a Markov simulation model for weather forecasting. A heuristic is proposed to solve the model to overcome the limitation of commercial solvers. Results indicate that accurate initial buffer calculations, depending on the production rate at the manufacturing ports and project-dependent characteristics, can increase the installation rate significantly for both strategies. Finally, feedering outperforms shuttling in most scenarios and is less weather dependent.

The continuous growth of international container trade calls for logistics networks that seamlessly connect cross-border, domestic, and local transport services. In the design of these networks with various hubs and modes of transport, the consideration of both economies of scale for multimodal transport and congestion is essential since they can significantly impact the location of the hubs and their size. Thereby, in this paper, we study these features within a multimodal hub location problem for international trade that considers a hierarchy in the network structure. We develop a mixed-integer linear programming formulation, minimizing infrastructural, operational, and congestion costs. A hybrid adaptive variable neighborhood search algorithm with tailored operators and speed-up strategies is proposed to solve large-scale instances. Numerical experiments are conducted for China's New Western Land-Sea Corridor case and provide new managerial insights for designing hierarchical, multi-modal, cross-border logistics networks.

Digital technologies are essential tools that enable traceability in supply chains. In low-income countries, traceability represents a challenge due to the complicated structure of supply chains and the involvement of multiple stakeholders. This research developed a framework for a digital traceability system (TS), using the Ethiopian coffee supply chain as a case study. A literature review was conducted to gain an in-depth understanding of state-of-the-art digital traceability technologies. A logistics audit was conducted to map the coffee supply chain in Ethiopia and evaluate the implementation level of traceability technologies. Although the implementation of traceability technologies in the Ethiopian coffee supply chain is low, the results revealed that the usage of traceability technologies improves downstream of the supply chain. The traceability framework developed in this study ranges from a paper-based TS to a fully digitalised TS. The implementation of a TS in the coffee supply chain of Ethiopia is met with several challenges such as affordability, limited awareness, resistance of certain stakeholders, infrastructure limitations, restricted accessibility of some technologies and insufficient policy frameworks. Stakeholders from low-income countries can use the framework developed in this study to adopt a TS for their supply chains in line with their needs and current digitalisation levels.

The emergence of Intelligent Transportation Systems (ITS) for freight transport in recent times has created interest among practitioners and researchers to extend freight ITS to support broader logistics processes, including dynamic tour scheduling, loading and unloading, warehousing, and even production. However, connecting transport data, ITS and logistics information systems require collaboration between different organizations and new business models to create business value for logistics actors. It is critical for these stakeholders to consider how their business models connect to create meaningful new data-to-information value chains. This study develops a conceptual framework to identify opportunities for logistics value creation with freight transport data. Building on the literature we construct a framework that reconciles multi-firm and firm-level business modelling. The main component is a generalized framework for Data-to-Value (DtV) chains for applications in information and communications technology. In order to support its business validity, we extend this framework with Business Model Canvases (BMCs) of the actors in the value chain. Three real-life use cases from a freight ITS community in the Netherlands are used to evaluate and illustrate the framework.

Electric Road Systems offer dynamic charging infrastructure for electric trucks, by means of overhead lines or rails that conduct electricity, or through induction loops in the pavement. Charging trucks while they are moving has important advantages over stationary charging, as batteries can be smaller and drivers and cargo do not have to wait while recharging. There are significant knowledge gaps about optimal network sizes, impacts on different stakeholders and cost/benefits of these technologies. This paper summarizes 4 MSc thesis projects on these topics by students of TU Delft. Their findings support the growing insight that ERS could make the electric truck landscape more efficient than if based on stationary chargers alone.

Freight transport decarbonization is challenging due to the slow implementation of policies to meet climate goals. This paper analyzes the dynamics of the implementation of freight decarbonization measures. A System Dynamics model was developed and applied to the Brazilian freight system to simulate the use of more sustainable modes and means of transport, including electrification, increased use of biofuels, acceleration of fleet renewal, and modal shift. Significant emission reductions are found in the scenarios combining a shift to alternative modes and a rapid phase-out of diesel vehicles. Even so, the Brazilian freight sector's emission budgets towards limiting global warming to 1.5 °C and 2 °C will be depleted during the current and next decade, respectively. An absolute reduction of carbon emissions before 2050 seems unlikely. Besides confirming the need to study the dynamics of the freight system, the findings corroborate the urgency for stronger actions on freight decarbonization.

Micro-hubs are considered to be a potential solution to increase the consolidation of inner-city deliveries: in the City of Rotterdam it is a potential measure to increase the logistic efficiency in and around the planned zero-emission zone in the city center. When designing the configuration of micro-hubs in an urban setting multiple aspects should be considered, such as their location, the type of vehicles to operate them, and the business model to be adopted for their operation. And although the topic is much studied it remains difficult to predict how different micro-hub configurations affect the transportation system in terms of transport movements, number of travelled kilometers, etc. This paper describes the use of the Tactical Freight Simulator (TFS) to investigate the impact of micro-hubs on the transportation system in case they would be implemented at a wider scale across the city center, and make a comparison with the current state of last-mile delivery. The case study explores three different design aspects: location, type of vehicles (delivery robots, cargo bike, LEV), and the business model (individual/full collaboration). Results show that the largest reduction of vehicle kilometers can be achieved in the scenarios with full collaboration between the CEPs.

This chapter discusses the potential of spatial and urban planning interventions to help decarbonize freight transport activities. Against a background of continuing growth and individualization of demand, decarbonization of freight transport services is a daunting challenge. The pursuit of decarbonization can take place along different strategic lines including reduction of transport demand, a shift between modes of transport, increase of efficiency of vehicle movements, reduction of energy use of vehicles and reduction of the carbon content of energy. Instruments of collective or public freight planning that can support these strategies include land use planning for logistics activities, freight transport demand management, investments in freight transport infrastructure including ITS, and regulatory and financial policies. Based on the literature we explore the above relationships, leading to a simple conceptual framework that links the decarbonization strategies to the instruments of freight transport planning. Urgent areas of future work include the design of multi-strategy roadmaps to achieve decarbonization targets, and the assessment of the effectiveness of combined freight planning measures.