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By hosting significant amounts of extra-atmospheric dissolved gases, including geogenic CO2 and CH4, volcanic lakes provide relevant ecosystem services through the key role the aquatic microbial community in mediating freshwater carbon fluxes. In view of elucidating the mechanisms governing the microbial spatial distribution and the possible implications for ecosystem functioning, we compared the hydrogeochemical features and the microbial community structure of two adjacent stratified volcanic lakes (Lake Grande - LG and Lake Piccolo - LP). Water chemistry, gases and their isotopic composition were coupled with microbial pigment profiling, cell counting, and phylogenetic analyses. LP showed transparent waters with low concentrations of chlorophyll-a and the occurrence of phycoerytrin-rich cyanobacteria. LG was relatively more eutrophic with a higher occurrence of diatoms and phycocyanine-rich cyanobacteria. Considering the higher concentrations of CO2 and CH4 in bottom waters, the oligotrophic LP was likely a more efficient sink of geogenic CO2 in comparison to the adjacent eutrophic LG. The prokaryotic community was dominated by the mixothrophic hgcI clade (family Sporichthyaceae) in the LG surface waters, while in LP this taxon was dominant down to -15 m. Moreover, in LP, the bottom dark waters harbored a unique strictly anaerobic bacterial assemblage associated with methanogenic Archaea (i.e. Methanomicrobiales), resulting in a high biogenic methane concentration. Water layering and light penetration were confirmed as major factors affecting the microbial distribution patterns. The observed differences in the geochemical and trophic conditions reflected the structure of the aquatic microbial community, with direct consequences on the dynamics of dissolved greenhouse gases.

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., TU Delft OPEN Textbook, Air Transport & Operations, Transport Engineering and Logistics, Transport and Logistics, Game Lab

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., Transport and Logistics

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., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Logistics, Transport and Planning

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., Aerospace Transport & Operations, Transport and Logistics

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., Transport and Logistics

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., Air Transport & Operations, Transport and Logistics

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ )

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., Transport and Logistics

Saline-alkaline lakes of the East African Rift are known to have an extremely high primary production supporting a potent carbon cycle. To date, a full description of carbon pools in these lakes is still missing. More specifically, there is not detailed information on the quality of dissolved organic matter (DOM), the main carbon energy source for heterotrophs prokaryotes. We report the first exhaustive description of DOM molecular properties in the water column of a meromictic saline-alkaline lake of the East African Rift. DOM availability, fate and origin were studied either quantitatively, in terms of dissolved organic carbon (DOC) and nitrogen (DON) or qualitatively, in terms of optical properties (absorbance) and molecular characterization of solid-phase extracted DOM (SPE-DOM) through negative electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). DOM availability was high (DOC ∼ 8.1 mM in surface waters) and meromixis imprinted a severe quantitative and qualitative change on DOM pool. At the surface, DOM was rich in aliphatic and moderately in aromatic molecules and thus mirroring autochthonous microbial production together with photodegradation. At the bottom changes were extreme: DOC increased up to 5 times (up to 50 mM) and, molecular signature drifted to saturated, reduced and non-aromatic DOM suggesting intense microbial activity within organic sediments. At the chemocline, DOC was retained indicating that this interface is a highly reactive layer in terms of DOM processing. These findings underline that saline-alkaline lakes of the East African Rift are carbon processing hot spots and their investigation may broaden our understanding of carbon cycling in inland waters at large.

Little is known about the quantity and quality of dissolved organic matter (DOM) in waters from continental geothermal systems, with only a few reports available from the Yellowstone US National Park. In this study, we explored the chemodiversity of DOM in water samples collected from two geothermal hot springs from the Kenyan East African Rift Valley, a region extremely rich in fumaroles, geysers, and spouting springs, located in close proximity to volcanic lakes. The DOM characterization included in-depth assessments performed by negative electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Reduced, saturated and little aromatic DOM compounds were dominant in the hot spring waters collected from either the Ol Njorowa gorge (ON) or the south shore of the soda-saline Lake Elementaita (ELM). Oxygen-poor and sulfur-bearing DOM molecules prevailed in ON, probably reflecting abiotic sulfurization from sulfide-rich geofluids. Nitrogen-bearing aliphatic and protein-like molecules were abundant in ELM, possibly perfusing through the organic-rich sediments of the adjacent Lake Elementaita. Notably, the heat-altered DOM of ancient autochthonous derivation could represent an overlooked source of aliphatic organic carbon for connected lentic environments, with a potential direct impact on nutrient cycling in lakes that receive geothermal water inputs.

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., Transport and Logistics

Polyphenols are natural antioxidant compounds ubiquitously found in plants and, thus, ever present in human nutrition (tea, wine, chocolate, fruits and vegetables are typical examples of polyphenol-rich foods). Widespread evidence indicate that polyphenols exert strong antioxidant, anti-inflammatory, anti-microbial and anti-cancer activities, and thus, they are generally regarded to as all-purpose beneficial nutraceuticals or supplements whose use can only have a positive influence on the body. A closer look to the large body of results of years of investigations, however, present a more complex scenario where polyphenols exert different and, sometimes, paradoxical effects depending on dose, target system and cell type and the biological status of the target cell. Particularly, the immunomodulatory potential of polyphenols presents two opposite faces to researchers trying to evaluate their usability in future cancer therapies: on one hand, these compounds could be beneficial suppressors of peri-tumoral inflammation that fuels cancer growth. On the other hand, they might suppress immunotherapeutic approaches and give rise to immunosuppressive cell clones that, in turn, would aid tumor growth and dissemination. In this review, we summarize knowledge of the immunomodulatory effects of polyphenols with a particular focus on cancer microenvironment and immunotherapy, highlighting conceptual pitfalls and delicate cell-specific effects in order to aid the design of future therapies involving polyphenols as chemoadjuvants.

Microbial electrochemical systems (MES) represent an innovative reagent-free technology for in situ remediation of groundwater contaminated by petroleum hydrocarbons. Here we describe the long-term (>160 days) anaerobic treatment of synthetic groundwater containing toluene (25 mg L-1) in a novel laboratory-scale, continuous-flow bioelectrochemical reactor, termed the "bioelectric well". Under optimal operating conditions (i.e., anode potential potentiostatically controlled at +0.2 V vs. SHE and recycle flow-rate set at 75 mL min-1), the observed electrogenic toluene oxidation rate was 67.2 ± 5.7 mg L d-1, a value which is among the highest reported in the literature for laboratory-scale anaerobic treatment systems. Correspondingly, electric current was 5.1 ± 0.1 mA and the Coulombic efficiency (i.e., the yield of toluene conversion into electric current) was 79 ± 7%. Electrogenic toluene oxidation was most likely catalyzed by Geobacter species, which were found to dominate the surface of the graphite anode. The combined application of GC-MS (for detection and identification of metabolites) and qPCR (for quantification of functional genes) revealed that toluene degradation was initiated by fumarate addition, an activation pathway that is widely distributed among anaerobic hydrocarbon-degrading microorganisms. Collectively, the results of this study indicate that the bioelectric well holds remarkable potential for in situ treatment of groundwater contaminated by petroleum hydrocarbons.

Background Recent studies have suggested that addition of electrically conductive biochar particles is an effective strategy to improve the methanogenic conversion of waste organic substrates, by promoting syntrophic associations between acetogenic and methanogenic organisms based on interspecies electron transfer processes. However, the underlying fundamentals of the process are still largely speculative and, therefore, a priori identification, screening, and even design of suitable biochar materials for a given biotechnological process are not yet possible. Results Here, three charcoal-like products (i.e., biochars) obtained from the pyrolysis of different lignocellulosic materials, (i.e., wheat bran pellets, coppiced woodlands, and orchard pruning) were tested for their capacity to enhance methane production from a food waste fermentate. In all biochar-supplemented (25 g/L) batch experiments, the complete methanogenic conversion of fermentate volatile fatty acids proceeded at a rate that was up to 5 times higher than that observed in the unamended (or sand-supplemented) controls. Fluorescent in situ hybridization analysis coupled with confocal laser scanning microscopy revealed an intimate association between archaea and bacteria around the biochar particles and provided a clear indication that biochar also shaped the composition of the microbial consortium. Based on the application of a suite of physico-chemical and electrochemical characterization techniques, we demonstrated that the positive effect of biochar is directly related to the electron-donating capacity (EDC) of the material, but is independent of its bulk electrical conductivity and specific surface area. The latter properties were all previously hypothesized to play a major role in the biochar-mediated interspecies electron transfer process in methanogenic consortia. Conclusions Collectively, these results of this study suggest that for biochar addition in anaerobic digester operation, the

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.

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.

In this paper we present an allocation model for a particular container supply chain where multiple sea-terminal quays and an inland terminal are considered. From the moment a container is unloaded from the vessel at the sea-terminal, several options for the nal transportation to the hinterland can be considered: trucks, trains and barges. The logistic planner decides which is the best allocation for the containers to the available eet. The objective is to minimize the transportation costs while guaranteeing a high service level. In general, the planner tries to bundle as many containers as possible and load them on barges or trains. Nevertheless, time constraints, such as due dates and dierent arrival times, make the bundling tricky and force the allocation to faster, more exible and more expensive modes of transport as trucks. We build a model for this setting, which has its roots in the classical Heterogeneous Fleet Vehicle Routing Problem (HVRP). We propose a case-study of an inland terminal in the Netherlands, whose data-sets are processed and solved by means of a Markov chain Monte Carlo heuristic. We explain in detail the characteristics of the dierent decisions and we provide insights for the real-world application.

In this paper we present an allocation model for a particular container supply chain where multiple sea-terminal quays and an inland terminal are considered. From the moment a container is unloaded from the vessel at the sea-terminal, several options for the nal transportation to the hinterland can be considered: trucks, trains and barges. The logistic planner decides which is the best allocation for the containers to the available eet. The objective is to minimize the transportation costs while guaranteeing a high service level. In general, the planner tries to bundle as many containers as possible and load them on barges or trains. Nevertheless, time constraints, such as due dates and dierent arrival times, make the bundling tricky and force the allocation to faster, more exible and more expensive modes of transport as trucks. We build a model for this setting, which has its roots in the classical Heterogeneous Fleet Vehicle Routing Problem (HVRP). We propose a case-study of an inland terminal in the Netherlands, whose data-sets are processed and solved by means of a Markov chain Monte Carlo heuristic. We explain in detail the characteristics of the dierent decisions and we provide insights for the real-world application.

In this paper, we extend the classical Variable Size Bin Packing Problem (VS-BPP) by adding time features to both bins and items. Speciffically, the bins act as machines that process the assigned batch of items with a fixed processing time. Hence, the items are available for processing at given times and are penalized for tardiness. Within this extension we also consider a stochastic variant, where the arrival times of the items have a discrete probability distribution. To solve these models, we build a Markov Chain Monte Carlo (MCMC) heuristic. We provide numerical tests to show the different decision making processes when time constraints and stochasticity are added to VSBPP instances. The results show that these new models entail safer and higher cost solutions. We also compare the performance of the MCMC heuristic and an industrial solver to show the effciency and the effcacy of our method.