This book serves as a comprehensive roadmap for navigating the realm of Operations Research (OR). From laying down fundamental mathematical principles to crafting precise modeling techniques and their solution methods, it culminates in a panoramic view of OR models mirroring real-world operations. Delving into diverse applications-from assignment problems to network problems like graph coloring and minimum spanning trees, and navigating through routing problems that are very common in logistics-the book equips readers with practical insights. Each model is accompanied by meticulously detailed examples, seamlessly integrated with hyperlinked codes accessible via an open repository. Moreover, it introduces an engaging dimension with hyperlinks to three serious games replicating some cornerstone OR models, offering a playful yet educational environment for solo or group experimentation.@en

In recent years, the highly fragmented multimodal transport offer in several countries has required the integration of these services by logistics service integrators (LSIs). The challenge for LSIs is to set up multimodal transport corridors that can respond efficiently to the heterogeneous demand of shippers and that are cost- and price-competitive against other transport solutions. We develop a bi-level programming model to assess the corridor's pricing and the service network design simultaneously. In the upper level, the model maximizes the profit of the LSI by designing the service network and implementing shipment-based pricing for paths adapted to the heterogeneous demand for transport services. In the lower level, the total cost of shippers in the network who choose services according to their preferences is minimized. We solve the model using reformulation and linearization techniques. Computational experiments based on the real-world case of the New Western Land-Sea Corridor in China are conducted to demonstrate the proposed model and to draw managerial insights. The results show that the shipment-based pricing strategy is beneficial for the LSI to obtain profit increases when considering the shippers’ heterogeneous preferences on time and reliability. The results also revealed that the service design and pricing decisions of the LSI are not only related to operational costs but also depend on the competitors’ offers in the market. Moreover, the impact of the level of frequency discretization, waiting time cost, the penalty cost for not fully utilized services, and the generalized cost of the no-purchase option on the decisions of the LSI are also investigated in the sensitivity analysis.@en

We study a typical daily drayage problem concerning the last-mile logistics at seaports for inland container supply chains. A set of trucks available at an inland container terminal must fulfil shippers’ requests of transporting containers within time windows and, to do so, can perform multiple daily trips. A request may entail picking up or delivering containers either at the shippers’ premises, the inland terminal or the seaport. Demand for empty containers can be satisfied by either using the available limited stock at the inland terminal, by street-turning or, ultimately, by retrieving them at a local depot for empties resulting in extra mileage. Hence, the minimization of routing costs also entails synchronizing trucks’ trips that retrieve and add empty containers to the inland terminal stock to avoid unnecessary visits to the empty depot. After modelling the problem mathematically, we develop an exact column-and-row generation approach embedded in a branch-and-price framework. To accelerate the solving process of the pricing problem, we propose effective strategies by combining a set of tailored pricing algorithms. These strategies perform well on a set of adapted Solomon's instances up to 100 nodes and against a standard branch-and-cut solver. Finally, experiments on real-world instances, inspired by a case study of an inland terminal at the Port of Rotterdam region, provide insights into current planning practices.@en

The construction of offshore wind farms requires solving more and more complex logistical problems due to the increasing sizes of turbines and changing environments. In particular, the installation of substructures requires attention due to their significant impact on capital expenditures and the limited literature and guidelines available. In this paper, we develop a decision support tool consisting of a discrete-event simulation that allows for comparing strategies for the installation of offshore wind turbine substructures in terms of time and costs. We identify several combinations of transportation and installation strategies for monopile and for jacket substructures. The differentiation is based on the deployed vessels and the installation sequence of the components. The strategies are applied to the case of a wind farm in the North Sea. For both substructure types, we find that strategies involving a second installation vessel result in the shortest installation times, and those in which the installation vessel(s) take(s) care of both transportation and installation result in the lowest costs. Additionally, we quantify the performance increases as a result of a reduction of the most prominent bottlenecks and the sensitivity of the project performance to the start date. Finally, the results are discussed in relation to future market and technological developments in the field.@en

We study a typical problem within the air cargo supply chain, concerning the transportation of standard Unit Load Devices (ULDs) from freight forwarders’ to ground handlers’ warehouses. First, ULDs are picked up by a set of available trucks at the freight forwarders’ premises within a time window. Next, they are delivered to the ground handlers, also within a time window, and discharged according to a Last In First Out (LIFO) policy. Due to space constraints, ground handlers have limited capacity to serve the trucks and waiting times may arise, especially in case freight forwarders do not coordinate their operations. Therefore, in this paper we consider a cooperative framework where this transportation is coordinated by a central planner. The goal of the planner is to find a proper routing and scheduling that minimizes the sum of the transportation and waiting times at the ground handlers’ warehouses, while satisfying the capacity of the trucks. We propose two mathematical formulations, one based on the routing and the other based on the packing aspect of the problem. To solve large instances of the problem, an Adaptive Large Neighborhood Search algorithm is also developed. With numerical experiments, we compare the performances of the two models and the metaheuristic, and we quantify the benefits of the proposed framework to reduce waiting times.@en

In this paper, we will study a typical problem in inland container shipping, concerning the barge transportation of maritime containers between a dry port and a set of seaport terminals. The barges depart from the dry port and visit a set of sea terminals, where containers need either to be dropped off or picked up. The goal is to achieve economies of scale with barges and avoid trucking as much as possible. The decision thus involves finding the best allocation of containers to barges in order to guarantee on-time delivery and meet capacity restrictions. The problem will be modeled as a variant of the split vehicle routing problem with simultaneous pickups and deliveries coupled with time features. The model includes parameters that can be tuned to improve barge utilization and travelling distance. A hybrid local search meta-heuristic algorithm, combined with a branch-and-cut solver, will be developed to solve the model. Numerical experiments have been conducted to test the performance of the algorithm and provide solution analysis for practical insights. Real-world data has been collected from a local barge operator based in the Port of Rotterdam region and will be used as input for the experiments. This will result in an in-depth analysis into current planning practices. The proposed framework complements existing models in the literature and contributes to the development of a comprehensive set of decision support tools, which help in the decision-making process for inland terminals.

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The typical voyage of a barge transporting maritime containers inland, consists of visiting a set of terminals where loading/unloading operations occur. The required stowage plans must meet stability requirements during all transport phases and avoid costly re-handling operations. In this paper, we formalize this problem and consider a typical dry-port transport system. We propose a comprehensive mathematical model that seeks to maximize stowed containers. To solve it, we develop a hybrid metaheuristic approach, based on local search and an industrial solver. Numerical experiments, based on real-world data, provide insights into the performances of the proposed framework and current stowage practices.@en

Offshore wind energy is recognised globally as a viable alternative to finite energy sources. However, large cost reductions are still needed, particularly in the Operations & Maintenance (O&M)phase, which currently accounts for about 30% of the cost of offshore wind. For large component replacements, a jack-up vessel is often leased from the spot market, resulting in high costs and low utilisation. These costs can be lowered when multiple wind farm service providers would share the resources needed to employ jack-up vessels. In this paper, we analyse two types of resource sharing, as an alternative to each service provider leasing its own vessel: (i)vessel purchasing and sharing and (ii)the combined use of vessel and harbour sharing. We design a simulation model and include stochastic processes such as weather patterns and component failures. Results show that cost benefits up to 45% can be achieved compared to a leasing policy, depending on the number of wind farm service providers involved and on the geographical distance between offshore wind farms. Moreover, it is shown that the jack-up vessel should not be fully utilised to minimise costs. The performance benefits of harbour sharing in addition to vessel sharing are generally small, but become more significant if the network faces considerable congestion. Results are illustrated using a case study based on a setting in the Western North Sea.@en

Increase of congestion at container deep seaports and shortage of capacity has led inland transport systems worldwide to rely more and more on inland terminals, and on the use of high capacity modes of transport to generate economies of scale and reduce negative effects of trucking. In this setting, planning the transport of maritime containers between a deep seaport and a final inland destination must also consider due dates and soft time windows, the latter known as Demurrage and Detention (D&D). In this paper, we formalize the concept of D&D, model the multimodal planning problem, and assess the impact of different D&D regimes on the emerging inland transport systems. By means of an experimental framework, we compare different D&D policies and provide managerial insights. The experiments highlight the effects of existing D&D regimes on transport efficiency and provide guidelines for their choice in practice. D&D are shown to have a twofold effect: first to limit consolidation opportunities and force the use of trucks as buffer, and second to push containers to dwell unnecessarily at the seaports.@en

In this paper, we present a DSS that generates schedules for the transportation of containers by barge in the hinterland, in particular from sea terminals to an inland terminal. As a case study, we propose the transportation from the ports of Rotterdam and Antwerp to a terminal in the south of the Netherlands, where the problem is typical. This problem is modeled as a heterogeneous fleet vehicle routing problem. The main decision is based on the trade-off of either consolidating containers to generate economies of scale with barges or alternatively dispatch, expensively and quickly, single containers by truck. The DSS is flexible as it can be applied to different settings by properly tuning the several parameters in the model. With numerical experiments, based on real world data, we evaluate the effectiveness of this system and its applicability.@en

The increase in traded container volumes worldwide puts pressure on the hinterland road network, leading congestion and emission problems. This leads to a requirement to develop intermodal transportation systems. In this chapter, we analyze the most important features of such container transportation systems for the hinterland supply chain. At the network design level, we review the current state of the art and we identify avenues for future research. Among others, we highlight that the coordination of container shipments across the container supply chain is a particularly relevant issue as hinterland networks involve several actors. At the operational level, we characterize the most important factors influencing the trade-off between intermodal transportation and truck-only deliveries. In addition, we provide a case study of coordination at an intermodal barge terminal in the Netherlands. We highlight that the exchange of information is the key enabler for efficient hinterland intermodal transportation and we show that a better information system can be of crucial importance.@en