Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit linkages of methodology to technological advances and analysis of worst case or average case performance of heuristics.
In this paper, the nonlinear interaction of regular water waves propagating over a fixed and submerged circular cylinder is numerically studied. At the structure’s lee side, the free surface profile experiences strong nonlinear deformation where the superharmonic free wave generated can be significant and is superposed on the transmitted wave. The wave profile then becomes asymmetric and skewed and may eventually reach the point of physical wave breaking. The governing equation and boundary conditions of this wave–structure interaction problem are formulated using both the fully nonlinear and the weak-scatterer theory. The corresponding boundary value problem is numerically solved by the immersed-boundary adaptive harmonic polynomial cell solver. In this study, a pragmatic wave-breaking suppression model is incorporated into the original solver. Both the harmonic free wave amplitudes at the structure’s lee side and the harmonic vertical forces on the cylinder are studied. The simulated harmonic wave amplitudes are compared to other published experiments and theoretical data. In general, good agreement is achieved. The effects of the incorporated wave-breaking suppression model on the simulated results are discussed. In our study, the incorporation of the pragmatic wave-breaking suppression model successfully extends the capabilities of the original fully nonlinear immersed-boundary adaptive harmonic polynomial cell solver.
Due to the increasing impacts of ships pollutants on the environment and the preventive laws that are tightening every day, the utilization of all-electric ships is a recent emerging technology. Being a promising technology, the usage of fuel cells as the main energy resource of marine vessels is an interesting choice. In this article, an all-electric hybrid energy system with zero emission based on fuel cell, battery, and cold-ironing is proposed and analyzed. To this end, actual data of a ferry boat, including load profiles and paths, are considered to assess the feasibility of the proposed energy system. The configuration of the boat and energy resources as well as the problem constraints are modeled and analyzed. Finally, the boat's energy management in hourly form for a one-day period is implemented. The improved sine cosine algorithm is used for the power dispatch optimization, and all models are implemented in MATLAB software. Based on the analysis results, the proposed hybrid system and the energy management method have high performance as an applicable method for the marine vessels. In addition, to be a zero-emission ship, the proposed system has an acceptable energy cost.
The shipping industry is associated with approximately three quarters of all world trade. In recent years, the sustainability of shipping has become a public concern, and various emissions control regulations to reduce pollutants and greenhouse gas (GHG) emissions from ships have been proposed and implemented globally. These regulations aim to drive the shipping industry in a low-carbon and low-pollutant direction by motivating it to switch to more efficient fuel types and reduce energy consumption. At the same time, the cyclical downturn of the world economy and high bunker prices make it necessary and urgent for the shipping industry to operate in a more costeffective way while still satisfying global trade demand. As bunker fuel bunker (e.g., heavy fuel oil (HFO), liquified natural gas (LNG)) consumption is the main source of emissions and bunker fuel costs account for a large proportion of operating costs, shipping companies are making unprecedented efforts to optimize ship energy efficiency. It is widely accepted that the key to improving the energy efficiency of ships is the development of accurate models to predict ship fuel consumption rates under different scenarios. In this study, the ship fuel consumption prediction models presented in the literature (including the academic literature and technical reports, which are a typical type of “grey literature”) are reviewed and compared, and models that optimize ship operations based on fuel consumption prediction results are also presented and discussed. Current research challenges and promising research questions on ship performance monitoring and operational optimization are identified.
The accelerated melting of the Arctic ice leads to the navigation of the Northern Sea Route (NSR) linking Asia and Europe, shortening transport channel between China and the European Union (EU). This has a significant impact on the China-EU bilateral trade which is analyzed in the present study. We present a framework based on a general equilibrium model for analyzing the impact of the NSR on the trade and the economies of China and the EU. Different fuel cost scenarios, consisting of fuel prices and sailing speeds on ice, are also considered. Specifically, we measure the changes in shipping costs between China and the EU, brought about by NSR navigation. These are used as a basis to quantify changes in transport technology. The Global Trade Analysis Project (GTAP) model is used to predict the trade and economic impacts. The results show that the NSR can save 0.98% in shipping costs and generate an increase in the exports of China and the EU in the order of 14,986 and 8,228 million US dollars, respectively. Among these exports, the mining industry shows the fastest growth, while the electronics industry experiences the largest increase in trade volume. Our findings reveal the potential of the NSR as an alternative route and its positive impact on bilateral trade between China and the EU. The results can provide a basis for shipping companies and governments to make decisions regarding the use of Arctic routes.
The real-time provision of high-quality estimates of the ocean wave parameters at appropriate spatial resolutions are essential for the sustainable operations of marine structures. Machine learning affords considerable opportunity for providing additional value from sensor networks, fusing metocean data collected by various platforms. Exploiting the ship-as-a-wave-buoy concept, this article proposes the integration of vessel-based observations into a wave-nowcasting framework. Surrogate models are trained using a high-fidelity physics-based nearshore wave model to learn the spatial correlations between grid points within a computational domain. The performance of these different models are evaluated in a case study to assess how well wave parameters estimated through the spectral analysis of ship motions can perform as inputs to the surrogate system, to replace or complement traditional wave buoy measurements. The benchmark study identifies the advantages and limitations inherent in the methodology incorporating ship-based wave estimates to improve the reliability and availability of regional sea state information.
This paper presents a study focused on wave spectrum estimation in practical scenarios where multiple ships operate in the same geographical area, potentially forming a network of wave recorders. A novel methodology is proposed to improve the accuracy and precision of the wave spectrum estimates, by combining sea state estimation methods and techniques for tuning the wave-to-motion transfer functions. The framework of the wave buoy analogy is used to derive estimates for each ship through the use of measured ship motion data and available initial estimates of transfer functions. Simultaneously, the wave-to-motion transfer functions of the individual ship are tuned by utilizing a weighted version of the wave data inferred on board the other ships in the network. The overall architecture of the procedure is modular, in the sense that various approaches may be implemented for obtaining sea state estimates and tuned transfer functions. The methodology is demonstrated through two case studies, one based on simulated vessel responses, and the other using model test data of ship motions in a wave tank. Both case studies consider a network of three ships in long-crested waves equipped with a dynamic positioning system. It is shown that the procedure provides good wave spectrum estimates, and leads to reduced uncertainty in the estimates via tuning of the vessel transfer functions.
Unmanned surface vehicles (USVs) are increasingly appealing for gathering metocean data, including directional sea spectra. This paper presents new developments towards estimating the response amplitude operators (RAOs) of surface vehicles equipped with inertial sensors. The novel approach undertakes the data-driven estimation of vehicle models of the wave-induced heave, roll, and pitch motion dynamics, as required to perform subsequent seakeeping computations. Specifically, a genetic algorithm executes the calibration of available closed-form RAOs for a simplified geometry. The algorithm makes a population of model-fitting parameters evolve towards minimising discrepancies between the predicted and measured response spectra in stationary operational conditions. Trust in the model is eventually increased by screening and merging the best-fitting solutions. Resulting response predictions using high-resolution spectral wave data for the AutoNaut USV demonstrate satisfactory accuracy and robustness in heave and pitch but a worse fidelity in roll, thereby motivating follow-up studies to improve the estimation of roll RAOs.
This article seeks to provide a sociological understanding both of the logistics service field and of the impact the COVID-19 pandemic has had on this field. To address this issue, we analyze the case of logistics services used by the shipping industry to manage maritime safety, namely statutory and classification services. These services verify the compliance of shipping vessels with private and public safety norms. We develop the Bourdieusian concept of nomos, according to three dimensions: A normative framework, a legitimate vision, and structural divisions. The findings highlight a complex set of industrial and regulatory norms which give rise to complementary and sometimes overlapping obligations. Nomos materializes as some actors, typically IACS member societies, benefit from an uncontested legitimacy to deliver such services, whereas other actors are excluded for a variety of reasons.
Danish seine is an active fishing gear targeting demersal species, such as European plaice (Pleuronectes platessa, hencefort referred as plaice), a commercially important fish species in the North Sea, Skagerrak, Kattegat, and Baltic Sea. Danish seining is a relevant fishery in relation to exemption from the European Union landing obligation. Trials were conducted from a commercial fishing vessel during the summer with high air temperatures and sea salinity and marked salinity and temperature gradients (pycnocline). Video equipment was used to observe fish entering the seine. Captured fish were individually tagged and housed in livewells for ten days to observe short-term survival. Reflex impairments and external injuries were assessed after capture and at the end of the observation periods using reflex action mortality predictor (RAMP) and catch-damage index (CDI) methodologies. We found that plaice entered the seine late in the towing process and that 87 % of the assessed fish survived, after 10 days of observation. There was a significant difference in short-term survival curves for fish that had been subjected to more than 30 min of on-deck during the catch-sorting process relative to those that had remained on deck for 30 min or less. The association between the time on deck and RAMP scores after capture was also significant. External injuries were primarily minor bruises, fin fraying, and net marks and changed little from after capturing to the end of the observation period.