Search

This article describes the development of a deployable high-gain antenna (HGA) for the proposed Mars Cube One (MarCO) CubeSat mission to Mars. The antenna is a new folded-panel reflectarray (FPR) designed to fit on a 6U (10 ? 20 ? 34 cm3) CubeSat bus and support 8.425-GHz Mars-to-Earth telecommunications. The FPR provides a gain of 29.2 dBic with right-hand circular polarization (RHCP). Small stowage volume is a key advantage of the FPR design, as it only consumes ~4% of the usable spacecraft payload volume with a mass of less than 1 kg.

The random vibration spectra typically used in lab based simulations towards developing and validating optimized packages for distribution have been developed through past research that have studied global transport vibration environments. Approximately 67% of all the freight tonnage moved in the U.S. utilizes heavy duty Class 8 trucks. While the floor (suspension) based vibration simulation profiles for these types of trucks are available towards lab based simulation, there have been no studies investigating the impact of shelving and stacking systems typically used for optimization of freight stowage in truck trailers by many freight companies. It is important to quantify how these storage systems affect the vibration levels experienced by loads within the trailers. This study utilized data recorders to measure and analyze the vibration levels experienced by products placed on aluminum decking beams and steel decking tables commonly used for stacking of loads on truck trailers in less-than-truckload (LTL) freight. Random vibration profiles were measured from the aluminum decking beams, steel decking tables and floor of the truck trailers. The results of this study show that the vibration levels experienced by LTL cargo, when decking tables and beams are used for stowage, are significantly different in comparison to the commonly used International Safe Transit Association steel spring truck profile. Using the power density spectrums developed in this study, packaging engineers should be able to develop and/or validate optimum protective packaging systems for LTL cargo transportation in North America that implement such stowage practices.

High strain composites for coilable space structures can undergo micro-structural changes in the time period between stowage and deployment. These changes include the accumulation of residual stresses in response to curvature changes (stress-relaxation) and accumulation of damage, which may lead to rupture of high strain composites. Currently, the mechanisms that cause damage growth and failure are not well understood. In this study, new experimental approaches are explored for applying constant curvature changes, that replicate the stowage conditions while imaging the evaluation of cracks on the compression surface and of damage in the micro-structure of the test sample. The test temperature is raised to accelerate the failure process.

Stowage planning is at the essence of a maritime supply chain, especially for short sea Ro-Ro ships. This paper studies stowage optimisation of Ro-Ro ships with a focus on stability constraints and the applicability of models. The paper contributes to short sea Ro-Ro ship stowage in two ways. First, we propose an integrated approach of designing stowage models with the consideration of loading computers. Second, we present a mathematical formulation of the Ro-Ro Ship Stowage Problem with Ballast Water with a discretisation method, to generate an optimal stowage plan which meets stability requirements by means of the weight of cargoes instead of excess ballast water, i.e. excess fuel consumption. Computational tests based on empirical data indicate significant savings and potential of model application in the real world. Preliminary results show 57.69% ballast water reduction, equivalent to 6.7% fuel savings and CO2 reduction. Additional tests on instances with various cargo weight distribution and discretisation levels are conducted, and finally, improvements are suggested for further research considerations.

In IoT sensor networks, in the course of statistics accumulation, the statistics severance and stowage overhead may perhaps be augmented. Likewise, the dependability and steadiness of radar information need to be mentioned. Therefore in this research, Reliable and Consistent Data Collection Framework for IoT sensor networks is aimed. In this agenda, a group of applicant nodules are nominated depending upon the vitality suitability feature and bumper place accessibility. As soon as the information is detected at period interim t, it will be transferred to the nominated applicant nodule depending on the complete discrepancy rate. If the package inaccuracy amount at the sink nodule is greater than the brink rate, then the foundation will choose to direct the simulated statistics to a nominated group of applicant nodules. Through replication outcomes, we demonstrate that the suggested method verifies both the steadiness and idleness of statistics, thus resolving the trade-off. It also decreases the quantity of simulated statistics.

This study deals with the containership stowage problem, determining how to stow containers to the containership slots. To improve the containership operational efficiency and meet the containership seaworthy requirements, a basic model is proposed for the simplified containership stowage problem. And then, it is extended by incorporating more practical considerations, which are progressively embedded in extensive models for different scenarios. These integer linear programming models aim to minimize the number of overstows under the restriction of the mechanical factors, the physical structure, and the stowing rules. The experimental results show that the models have strong scalability for various scenarios.

The knapsack problem is preferred in analyzing area of stochastic & combinational extension with the intention of choosing objects into knapsack to avail maximum capacity while not increasing knapsack’s stowage. The main focus of this paper describes problem solving approach using genetic algorithm (GA) for the 0-1 knapsack problem. The experiments started with some initial value of Knapsack variables remain continue until getting the best value. This paper contains two sections: The first section contains concise description of the basic idea of GAs and the definition of Knapsack Problem. Second section has implementation of 0-1 Knapsack Problem using GAs.

Oil and gas are the main sources of Russian national wealth. Russia has the greatest reserves of oil and gas in the world. It gives the status of energy stowage of the Earth. This is especially true concerning natural gas. Transportation of natural gas from the gas field and its supply to the end user is carried out by means of pipelines.

Before the vessel arrives at the port, the export containers will be successively transported to the storage yard of the port by the truck fleet, waiting for loading. Such process is usually referred to as container collection. Generally, the collection of export containers will start in 3–5 days before the arrival of the corresponding vessel, and the containers will be transported by the external container trucks to the yard successively. The container collection will be closed in 6 h before the arrival of the vessel (the container will be stopped from entering the terminal), so that the final stowage of the vessel and the loading operation plan can be made according to the information of the collected containers.

Consolidation plan (CP) and stowage plan (SP) of coil ships are to assign steel coils onto ships and decide specific loading location for each coil, respectively, which are two correlative and adjacent plans in the finished product logistics of iron and steel industry. In this paper, we focus on the problem of making an integrated plan of CP and SP (C&SPP), which is important and rarely studied, to try to achieve systematic optimisation from the perspectives of the product terminal, shipping companies, and customers, simultaneously. First, according to the practical situation, an integer programming (IP) model is established to optimise ship loading, transportation timeliness, and operation efficiency. Then, to improve calculating efficiency, the IP model is simplified (SIP) by reducing the dimensions of variables. After that, based on the problem features and algorithm behaviour, an improved differential evolution algorithm is proposed in which an element-dependent strategy is designed to set control parameter, a guided operator is constructed to generate mutant individual and an iteration-based mechanism is introduced to dynamically adjust the parameter and mutation strategy, respectively. Finally, extensive experiments are carried out to evaluate the proposed method, and the numerical results demonstrate its effectiveness in solving practical scale C&SPP.

peer-reviewed Structures used in space applications demand the highest levels of stiffness for their mass whilst also performing in a hostile environment. To partly address these requirements and so as to also pack efficiently for stowage during launch we propose a new type of compact telescopic morphing lattice space boom. This boom stows within a 1U CubeSat volume and is lightweight being only 0.4 kg. The boom has a total length of 2 m in its deployed state which is 20 times its stowed height. The device comprises two multi-stable cylindrical composite lattices that are joined telescopically. These lattices nest inside one another in the stowed configuration, with the objective of improving packaging efficiency. Notably, prestress and lamina orientation are used to smoothly change shape from being compact when stowed to being extended when deployed. The lattices in the boom have been designed to maximise deployment force and to be self-deploying by tuning manufacturing parameters. As a result, only a small, lightweight mechanism is required to regulate deployment speed of the lattice boom. By reversing its direction, this mechanism can be used to retract the lattice boom to its stowed configuration, thereby enabling two-way reconfigurability.

Ultra Large Container Vessels (ULCV) with high trade volumes per port are making fewer calls per round trip with more transshipment cargo and more port times at higher costs. Innovations which increase handling productivity and streamline handling operations of feeder vessels (in short: feeders) are required to avoid inefficient long stays in ports as well as to reduce the costs resulting from ULCV processing. The patented “Integrated Terminal Ship System” (ITSS or ITS system) satisfies these requirements by the innovation of direct container handling between ULCV and feeder vessels. Basically, there are two technical solutions possible: Transshipment containers are simultaneously handled on both ULCV sides using two finger piers (first alternative) and im-/export containers are un-/loaded at the ULCV quayside while transshipment containers are directly handled between ULCV and feeders at the ULCV waterside using one finger pier (second alternative). Both ITSS system alternatives use traction engines which move on the finger pier(s). The engines facilitate direct handling of transshipment containers by shifting the feeder vessel(s) alongside the pier(s) to the respective container bays required as per stowage plans.

El objetivo de este trabajo es diseñar una metodología sobre los procedimientos de inspección de cada una de las siguientes operativas que se realizan en los puertos: carga/descarga de graneles líquidos: analizar todas las tareas que se deben realizar para una correcta inspección tanto en buque como en la terminal en tierra. bunkering: analizar todas las tareas que el inspector debe realizar en una operativa de repostaje de combustible tanto en el buque como en la gabarra suministradora. inspección de carga/descarga mediante peso por calados o “draft survey” de graneles sólidos: analizar el proceso para la determinación de la cantidad de producto cargado/descargado a través de los calados del buque. una vez realizado el análisis de todos los procesos se realizará el diseño de la metodología de inspección. este trabajo se basará principalmente en el trabajo de campo y la experiencia laboral de inspectores en el puerto de barcelona, con el debido apoyo de manuales homologados y normativas oficiales. el trabajo de campo permitirá conocer la implicación de todas las partes en el proceso (inspector, terminal, gabarras, laboratorios, consignatarios, compradores y vendedores) y todas las tareas que se deben realizar como inspector de una forma conjunta, mientras que los manuales y normas permitirán conocer de forma detallada cada uno de los procesos a realizar.

The Master Bay Plan Problem (MBPP), which is to decide the stowage plan of large containerships, has been studied since 1990. Since the size of containerships has been growing dramatically from 1970’s, this problem becomes one of the most important issues in shipping lines as the quality of a stowage plan affects the profit of the shipping lines significantly. Many different research works have been carried out to solve this problem, including mathematical modeling, decision support systems, rule-based expert systems and heuristic driven approaches. However, none of these works provide a satisfactory solution to the stowage planning problem. The focus of this project is to develop an automated multi-objective optimization stowage planning system which is capable of generating optimized stowage plans for large containerships in a short amount of time. Optimized stowage plans here refer to: (1) the number of unnecessary shifts of containers is minimized, hence the operation cost is reduced; (2) the amount of workload (both loading and unloading of containers) across the ship is well distributed for every port, thus the efficiency of quay cranes for handling the containers is improved; (3) the number of unusable container slots is minimized, therefore there are more space to load other containers; (4) the weight distribution of containers on the containership is well arranged, so that the amount of ballast used to balance the ship is reduced and the fuel oil requirement is reduced. The optimality of these objectives is difficult to be obtained simultaneously for one single stowage plan. Therefore instead of aiming to generate an optimal stowage plan for a containership, in this project a randomized block stowage algorithm with Tabu Search is proposed to obtain a set of stowage plans that emphasize on different objectives for the shipping lines, and help them make better decisions in the real world. An automated stowage planning system is developed in this project. A randomized block stowage algorithm with Tabu Search is proposed and implemented in this system. The basic idea of the block stowage algorithm is to divide the containers in groups and partition the containership into blocks. The algorithm breaks the stowage planning process into two stages: (1) obtaining a set of stowage plans by selecting different blocks combinations in a randomized manner; (2) applying Tabu Search to each of the stowage plans to adjust every container’s location in order to achieve an optimized final stowage plan. MASTER OF ENGINEERING (SCE)

KMP Marine Hawk II is one of the highspeed craft that operates in Riau Archipelago. It carries the passenger as well as cargo in breakbulk within the archipelago area. This study aims to determine the technical stability calculation of KMP Marine Hawk II using numerical computation with Maxsurf software IMO Criteria requires GZ Max is 15 deg. In the departure full load condition, the GZ max value is 37.3 deg. In the navigation on full load GZ max value is 32.7 deg. While in the arrival full load is 25.5 deg with lightship condition 29.1 deg. All of those GZ numbers are satisfying the criteria from IMO HSC 2000 Annex 8 Mono Hull. However, the ship crew should consider the passenger-cargo stowage to maintain those GZ criteria.

This paper studies the combined problem of container selection and stowage. Each container has information of original and destination ports and the value. A multi-objective programming model is established with the goal of maximizing the value of selected containers and minimizing the number of container rehandle operations during the whole route. In addition, a heuristic algorithm is proposed to solve large-scale instances. The experiments are carried out in JAVA. The results prove the validity of the model and the algorithm.

[ES] El objeto de este Trabajo Final de Máster es la elaboración de la acción preventiva de una empresa dedicada a la estiba de bobinas de pasta de papel en un puerto de la Comunidad Valenciana. Para ello, se hará una breve interpretación de la Ley 31/1996 y del Real Decreto 39/1997 con la intención de iniciar a la empresa en la integración de la prevención de riesgos laborales en su sistema de gestión. Posteriormente se procederá a la identificación de riesgos derivados del desarrollo de la actividad de estiba de bobinas de pasta de papel. A partir de la identificación de los riesgos se elaborará la evaluación inicial de riesgos y la planificación de las medidas propuestas. Además, con el fin de que la integración de la acción preventiva sea mayor, se incluirán las pautas formativas para los distintos puestos de trabajo encargados de la descarga de las bobinas de pasta de papel desde el buque y se elaborará un procedimiento de trabajo, para completar las medidas propuestas, que incluirán las acciones a realizar desde que el barco es amarrado y se inicia la actividad de estiba, hasta que se descargan y almacenan las bobinas de pasta de papel., [EN] The purpose of this Final master's work is to prepare the preventive action of a company dedicated to the stowage of paper pulp coils in a port of the Valencian Community. To this end, a brief interpretation of law 31/1996 and Royal Decree 39/1997 will be made with the intention of initiating the company in the integration of the prevention of occupational risks in its management system. Subsequently, the identification of risks arising from the development of the stowage activity of paper pulp coils will be identified. From the identification of the risks, the initial risk assessment and the planning of the proposed measures will be developed. In addition, in order that the integration of the preventive action is greater, the training guidelines for the different jobs in charge of the unloading of the pulp coils from the ship will be included and a work procedure will be elaborated, for complete the proposed measures, which will include the actions to be taken from when the boat is moored and the stowage activity begins, until the pulp reels are unloaded and stored.

Vehicle stowage is a central link in the process of logistics distribution. The distribution cost and transportation cost in the process of stowage account for a large part of the total logistics cost. Therefore, the key to reduce the logistics cost of enterprises is to carry out the stowage work reasonably. The whole cargo loading process involves three links: order, vehicle selection and loading. Firstly, distribution vehicles are allocated according to customer order information. Secondly, according to the distribution order of customer network nodes, the order of cargo packing is determined. Finally, distribution plan is worked out to determine the location and direction of cargo placement so as to maximize the utilization rate of vehicles. This paper mainly focuses on the order processing and vehicle selection in vehicle stowage. Using the pedigree clustering algorithm to cluster the nearest orders, the batch orders can be processed quickly and effectively. The vehicle selection algorithm is designed on the premise of considering the vehicle load, volume and fuel consumption. Finally, the effectiveness and feasibility of the algorithm are verified by a specific example.

The wide range of Maritime Dangerous Goods (MDG) usually have complex attributes and take high risks when transporting. In order to secure the transport, MDG must be strictly packed, segregated and stowed according to the International Maritime Dangerous Goods Code (IMDG Code). This paper aims to realize the intelligent management of MDG transport. Firstly, analyzes the MDG ontology and then describe the concepts, individuals, properties, the relationship between concepts and individuals of MDG in detail based on ontology. Furthermore, a method and model for constructing the knowledge graph of maritime dangerous goods (KGMDG) are proposed. Finally, its possible application is explored in this paper. The KGMDG is able to work out the correlation between goods, and provides technical support for intelligent inquiry of MDG knowledge and automatic judgment of stowage and segregation. It is of great significance for making the storage and transportation strategies, the emergency plans, and for preventing accidents caused by dangerous goods.

In this work, a rigidly foldable origami configuration is used to achieve easy stowage of an otherwise bulky Yagi-Uda dipole antenna. This antenna operates in the extended range mobile frequency band of 698 MHz to 806 MHz, enabling those in remote regions to have access to reliable mobile communications. Within this frequency range, the gain reaches a minimum of 4 dB and a maximum of 8 dB with a relatively unaffected 3 dB beamwidth.

As an important part of the vessel stowage planning, the Master Bay Plan Problem (MBPP) can effectively reduce the container's reverse operation and ship stay time, improve the transportation efficiency of container ships and the safety of the entire route if it rationally formulated. The essay established a mathematical model of container loading sequence with the target of minimizing the number of ship containers. The evolution strategy algorithm (ES) is used to optimize the container MBPP, and the two-dimensional real number coding method is designed. The two-point crossover interchange recombination and mutation method is used to analyze ES through different parent and child scales and multiple scale examples. Finally, the ES is compared with the commonly used optimization algorithm PSO and the heuristic algorithm based on the actual shipping problem. The results show that ES can find the optimal solution more quickly, and the optimization efficiency is higher than PSO and the heuristic algorithm of the actual ship loading problem. This consequence verified the validity of the model and algorithm.

In the past, most researchers focused on the storage space allocation problem or container block allocation problem in maritime container terminals, while few studied the container slot allocation problem in rail–water intermodal container terminals. Container slot allocation problem is proposed to reduce relocation operations of containers in railway container yards and improve the efficiency of rail–water intermodal container terminals. In this paper, a novel outbound container slot allocation model is introduced to reduce the rehandling operations, considering stowage plan, containers left from earlier planning periods and container departure time. A novel heuristic algorithm based on the rolling planning horizon approach is developed to solve the proposed problem effectively. Computational experiments are carried out to validate that the proposed model and algorithm are feasible and effective to enhance the storage effect. Meanwhile, some other experiments are conducted to verify that our approach is better than the regular allocation approach, which is a common method in marine and railway container terminals, and container weight is the most important influence factor when storing containers.

Thin-membrane deployable antenna is potentially suitable for the applications of large-aperture light-weight deployable phased array antenna due to its advantages of low-mass, deployment and small stowage volume. Thin-membrane deployable antenna will be widely applied in satellite or spacecraft. In this paper, the thin-membrane deployable antenna was designed, fabricated and tested. The results show a good agreement between measurement and simulation, along with an excellent performance.

In productive processes where parts are assembled, the assembly time is one of the most important problems that should be solved. Due to this, a case study was carried out in one company in the wooden sector, in which the Lean methodologies and the Discrete Events Simulation are integrated, to evaluate and improve the assembly processes of four-input wooden stowage. This study began by validating the process, then it was simulated in the Arena software, where great variability is observed in the assembly time of the four-input pallets, obtaining an average result of 25+/- 2 minutes. Due to this reason, the use of this methodology was proposed, applying the DMAIC cycle and carrying out controls in the process, it was possible to reduce it to 19 +/- 1 minute per stowage unit assembled, which meant a 24% reduction in the time spent manufacturing. All of this positively influenced the final delivery time of the product, so, with this new time, the company could satisfy the demand of its customers, and will be able to place its product on the market in less time.

The aim of the article is to investigate the number and assortment of training solutions required to perform technical operations involved in parachute packing and landing platform mounting and mooring. The article proposes a novel approach to the identification of the number and value of the attributes of technical operations, which takes into consideration objective information and expert assessment results. The article presents an algorithm aimed at the identification of the number and assortment of training solutions based on the algorithm of DBSCAN cluster analysis and promoting the calibration of expert assessments in order to improve clustering quality. The results of experimental research prove the feasibility of dividing technical operations into clusters whose quantity and composition are predicted by experts and are practically relevant.

This document presents the implementation of the methodology for the evaluation of non-metallic materials, through the modeling, simulation and diagnosis of components manufactured by the high-density polyethylene injection method called structural foam, where a mixture is made between an inert gas and polyethylene of two origins: a part of recycled material and the other part of new material. This type of manufacturing is carried out for the shaping of stowage-type components, for the transport of containers of liquid substances. For the evaluation of the Stowage, a simulation was carried out from a commercial modeling software, Autodesk Inventor, based on the geometry, the mixture of materials, the attachment points and border parameters, the location and type of loads to simulate, and the different ways in which the loaded stowage would be used. After this, mechanical tests were carried out to determine the properties of the materials in their different mixtures and a feedback process of the finite element model was carried out, thus obtaining results with a minimum error factor, and thus issuing a diagnosis, focused on which material mixing ratio was the most suitable, based on the critical points of the stowage, its stress and deformations, and its safety factor. Finally, the existence of imperfections (bubbles), typical of the manufacturing process, which tend to have an incidence as concentrators of intrinsic efforts, and as critical points, is considered.

Stowage planning is an activity of containers arrangement on container vessels. A good and fast container setup requires a piece of software that can help planner’s performance especially for multiport cases. The Case Based Reasoning method (CBR) can be used to implement software in order to produce a container setup based on pre-existing setups. The Case Based Reasoning method discussed in this paper is focused on the reuse phase by designing the Similarity algorithm, Container Loading List adaptation algorithms as well as the restow evaluation algorithm. The set of algorithms is used to automatically produce a container setup at each port in one voyage and display the number of restow and many containers that experience loading and unloading in one voyage so as to assist the performance of the planner in every port. The results of this study can also be analysed for the workload of planners where the smaller the case base population, manual swaps performed on average more than 70% of the total containers on the ship.

Deployable structures are an interesting option to replace mechanical systems in space applications, allowing a more efficient use of the limited space available for the payload. However, due to the probability of long stowage times in a retracted configuration, composite deployable structures are prone to suffer some type of relaxation phenomenon, which may compromise the deployment. This research describes how to implement a technique to assess the characterization of the relaxation behaviour of a material certified for space applications and its influence in the opening of a deployable elastic–hinge. The relaxation master curve of the material was determined using an accelerated experimental testing technique where temperature is used to promote accelerated ageing in the material. This data was then introduced in a finite element model. Finite element analysis was used to predict the deployment behaviour of the structure before and after the influence of material relaxation due to the stowage of the elastic–hinge for a certain period of time, using the relaxation master curve. The relaxation of the material led to an increase in the time necessary to complete the deployment. This is due to a significant reduction in the internal energy of the elastic–hinge.

To obtain an efficient and reasonable solution for slot allocation in rail-water container terminals, this paper develops storage optimal allocation model 1 to improve the yard space utilization, which is solved by a heuristic algorithm based on Tabu search. Model 2 is then built to reduce the relocation movements. A concept of fall-down problem in shunting operation plan is thus proposed to solve model 2. Models 1 and 2 are tested with numerical experiments. The results show that the yard space utilization increases by 50% approximately compared to the strategy of one train piling onto a fixed area called a subblock. Meanwhile the number of container relocation movements is less than five when using the fall-down problem strategy. Accordingly, the models and algorithms developed in this paper are effective to improve the yard space utilization and reduce the number of container relocation movements.

The growing of effective control of guards of Federal Firefighting Service of Emercom of Russia in case of fire fighting operations on ships is impossible without deep analysis of information which prospect of present practice of fire fighting of ships of various types of ships. Such differences are caused by features of space-planning and constructive solutions of courts, existence by the developed system of ventilation and air conditioning, character of fire loading, etc. that predetermines ways of transfer of heat at the fires, and also features of distribution of burning. In article information on practice of suppression of the fires on various types of vessel during stay them in ports is analyzed. From this analysis the conclusion is drawn that despite variety of types of vessel, the fires arising on them are conditionally divided into three groups: the fires in residential and service premises; the fires in machine and boiler departments; the fires in stowage spaces. Features of development of the fires in groups of ship rooms are considered. The analysis of information on the fires in courts also showed that scales and consequences of the fires depend on design features of courts, the transported freight, fire protection systems, concentration of necessary number of forces and means and on efficiency of the made decisions. It is noted that based on the carried-out analysis of information on the fires in the courts which are in ports of generalization of experience of suppression of the fires on various types of vessel and taking into account features of development of the fires in various groups of ship premises there are worked out “The recommendations for divisions of Federal Firefighting Service Emercom of Russia about suppression of the fires on land inshore facilities of the ports and courts which are at moorings and piers of seaports and on inland waterways” which application in practice shall promote increase in effective management of divisions of FPS Emercom of Russia in case of suppression of the fires.

Purpose The purpose of this paper is to propose robust optimization models addressing the container slot allocation problem with minimum quantity commitment (MQC) under uncertain demand, which is faced by international companies export to USA. Design/methodology/approach A novel robust optimization approach handling linear programming (LP) with right-hand-side uncertainty is developed by incorporating new parameters: uncertainty level, infeasibility tolerance and reliability level. Two types of uncertainty, namely, bounded uncertainty and symmetric uncertainty are considered, respectively. Findings The present work finds that the expected revenue increases as the uncertainty level and the MQC decrease, as well as the infeasibility tolerance and the reliability level increase, no matter which type of uncertainty is considered. Research limitations/implications Typically, the capacity constraints in a container shipping model should include two major restrictions: (1) number of slots and (2) total weight of loaded and empty containers. However, this study only addresses the first restriction for simplicity. It is recommended that future research explore the optimal solutions with additional restriction (2). Originality/value This paper fills a theoretical and practical gap for the problem of slot allocation with MQC in container liner revenue management. Deterministic and tractable mixed integer LP is formulated to derive robust solutions which immunes to demand uncertainty. Illustrative examples are presented to test the proposed models. The present work provides practical and solid advice and examples which demonstrates the application of the proposed robust optimization approach for logistics managers.

The ship stowage planning problem (SSPP) is a very complex and challenging problem in the logistics industries because it affects the benefits of both shipping lines and port terminals. In this paper, we investigate a multiobjective SSPP, which aims to optimize the ship stability and the number of rehandles simultaneously. We use metacentric height, list value, and trim value to measure the ship stability. Meanwhile, the number of rehandles is the sum of rehandles by yard cranes and quay cranes and all necessary rehandles at future ports. To solve this problem, a variant of the nondominated sorting genetic algorithm III (NSGA-III) combined with a local search component is proposed. The algorithm can produce a set of nondominated solutions. Decision makers can then choose the most promising solution for practical implementation based on their experience and preferences. Extensive experiments are carried out on two groups of instances. The computational results demonstrate the effectiveness of the proposed algorithm compared to the NSGA-II and random weighted genetic algorithms, especially when it is applied in solving the six-objective SSPP.

The behaviour of granular cargos transported by sea has not been sufficiently investigated yet from a theoretical perspective. International regulations controlling the loading and stowage of bulky cargos, despite some updating and improvement, remain empirical, lacking a solid theoretical foundation. In the paper is investigated the inception of roll instability for a vessel containing a rectangular hold partially filled with dry granular material, by applying a simulation approach based on coupled micro-scale modelling of particles with vessel motion. The method of molecular dynamics is employed, combined with a rudimentary model of vessel motion in beam seas. The key assumptions behind the modelling of cargo's movement are that, the granular material is dry, all particles are spherical and adjacent particles interact through non-linear elastic and frictional forces. Characteristic simulation results, including comparisons against cases of rigid cargo, are presented, pointing out cases where the agility of the cargo may have a positive or a negative effect on vessel's stability.

There has been significant growth in air transport worldwide, as well as in Brazil. However, studies have emphasized that disabled, obese, and elderly passengers face difficulties when using this means of transport. Among these difficulties, issues related to passengers’ own assistive devices, including damage, loss, or the impossibility of using during the entire flight, stand out. Therefore, the present study aims to understand the trends in assistive technology focusing on cabin design. This research is based upon literature review, interviews with manufacturers and research centers, visits to specialized trade fairs, and patent search. The results revealed a great diversity of assistive products, its trends, and an increase in their use, which affect aircraft cabin design, especially in terms of space, access, and stowage of these devices.

Stowage planning is a tedious job. It involves technical and administrative tasks. Evolving data along the process and information completeness should be considered, when dealing with the updating of stowage plans. Recent IMO Regulations have brought forward a set of advanced stability criteria, far beyond the computation of metacentric height. The paper outlines the challenges on the implementation of proper stowage planning practices from the perspectives of safety and operational efficiency.

The calculation of lashing forces on containerships is one of the most important aspects in terms of cargo safety, as well as slot utilization, especially for large containerships such as more than 10,000 TEU (Twenty-foot Equivalent Unit). It is a challenge for stowage planners when large containerships are in the last port of region because mostly the ship is full and the stacks on deck are very high. However, the lashing force calculation is highly dependent on the Classification society (Class) where the ship is certified, its formula is not published and it is different per each Class (e.g., Lloyd, DNVGL, ABS, BV, and so on). Therefore, the lashing result calculation can only be verified by the Class certified by the Onboard Stability Program (OSP). To ensure that the lashing result is compiled in the stowage plan submitted, stowage planners in office must rely on the same copy of OSP. This study introduces the model to extract the features and to predict the lashing forces with machine learning without explicit calculation of lashing force. The multimodal deep learning with the ANN, CNN and RNN, and AutoML approach is proposed for the machine learning model. The trained model is able to predict the lashing force result and its result is close to the result from its Class.

The transition of the railway industry from information management systems to systems with full management can be achieved by combining automated information systems integrated into production processes in the railway network. Russian Railways OAO acts as a driver for the development of modern technologies in the transport sector, aiming to increase efficiency in organizing the transportation process. Monitoring changes in customer needs, as well as focusing on increasing the value of services and products for consumers, including service quality improvement by digitalizing individual operations related to the cargo handling during loading, is becoming increasingly important. The introduction of the developed automated system for the preparation of technical specifications for the stowage and securing of cargo in rail cars and containers will increase production system organization quality in railway transport, as it will eliminate the incompetence, negligence and irresponsibility of workers associated with the handling, stowage and securing, reduce the time for preparing technical documentation, and improve the transport system operation quality. To achieve the stated goal, based on the studies, the author developed a computational decision-making procedure for the stowage and securing of cargo in the rail car, taking into account a possible two-coordinate shift. The procedure allows employees responsible for accepting cargo for transportation to assess the quality of the cargo securing according to the criterion of permissible shift at the initial stage of the transportation process. The developed automated system has many positive aspects. The security of the system significantly increases, the risk of errors is reduced, and the influence of the human factor is minimized. The complexity of the process of compiling a sketch of the stowage and securing of the cargo in the rail car loaded in accordance with the Technical Specifications is reduced. Most of the work is done by automated software, the cargo shipper has more time to control the loading process; time limits of various works and projects generally decrease.