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The stowage plan and the securing arrangement of non-standardized cargo are some of the most important aspects in terms of cargo safety and economic costs. For this reason, the optimization of this operation is crucial and a daily challenge for securing planners trying to fulfill both requirements. In the present paper, a new methodological optimization is proposed presenting novel mathematical models and new 3D maps useful for the people in charge of stowage and securing arrangement. For this goal, the materials followed were the Code of Safe Practice for Cargo Stowage and Securing (CSS) of the International Maritime Organization (IMO) because many ships' Cargo Securing Manuals refer to this international standard. Using an initial case study and making use of response surface techniques of design of experiments (DOE), multiple numerical simulations were performed to obtain novel mathematical models, revealing a high precision. Moreover, new 3D maps were presented and are very interesting tools due to their ease of understanding. The obtained results were compared with other simulations carried out where different variables were employed. The presented models of this methodology can predict the best securing arrangement to fulfill the balance forces in any stowage position (vertical and longitudinal) using the minimum securing devices and keeping the standards of safety. These methodological tools offer valuable advice to the shipping industry with responsibilities involved in the securing design of non-standardized cargo items. [ABSTRACT FROM AUTHOR]

The stowage plan and the securing arrangement of non-standardized cargo are some of the most important aspects in terms of cargo safety and economic costs. For this reason, the optimization of this operation is crucial and a daily challenge for securing planners trying to fulfill both requirements. In the present paper, a new methodological optimization is proposed presenting novel mathematical models and new 3D maps useful for the people in charge of stowage and securing arrangement. For this goal, the materials followed were the Code of Safe Practice for Cargo Stowage and Securing (CSS) of the International Maritime Organization (IMO) because many ships’ Cargo Securing Manuals refer to this international standard. Using an initial case study and making use of response surface techniques of design of experiments (DOE), multiple numerical simulations were performed to obtain novel mathematical models, revealing a high precision. Moreover, new 3D maps were presented and are very interesting tools due to their ease of understanding. The obtained results were compared with other simulations carried out where different variables were employed. The presented models of this methodology can predict the best securing arrangement to fulfill the balance forces in any stowage position (vertical and longitudinal) using the minimum securing devices and keeping the standards of safety. These methodological tools offer valuable advice to the shipping industry with responsibilities involved in the securing design of non-standardized cargo items.

This paper reassesses the maritime Southeast Asian forest and marine commodities trade from the sixteenth century to World War I. The 'Macassan' traders who visited northern Australia were primarily from Makassar and southern Sulawesi (including Bugis, or Bajau and Sumbawan immigrants) and the Lesser Sunda Islands (to where these ethnic groups had migrated) but also included the Indigenous Australians who accompanied them on their voyages. Research into other ethnic groups (Chinese, Makassar-Malay, Seram Laut Islanders, Solorese and Timorese mariners) also associated with both northern Australia and the maritime Southeast Asian forest and marine trade suggests that they be included in the 'Macassan' group. Analysis of historical sources for the late nineteenth–early twentieth century Macassan trepang (sea cucumber) industry in north Australia demonstrates that perahu spare cargo capacity was filled with additional commodities when the trepang harvest was low, ensuring voyage profitability. Comparison of the maritime Southeast Asian trade with ethnographic, archaeological, historical, and linguistic evidence in northern Australia, suggests that 20 commodities were likely to have been exported from the latter, seven of which have never before been mentioned in the literature. Mapping of the Macassan routes transporting the 20 commodities shows that northern Australia was connected to a vast network of maritime Southeast and East Asian trade with global reach. The importance of these findings for Asian contact archaeology in northern Australia is threefold: (1) archaeologists should look beyond ceramic provenance, metal, and glass to seek material and chronological evidence for the extraction and processing of a wider range of forest and marine commodities; (2) evidence for the extraction of particular commodities might be a proxy for age estimation of a site; and (3) the origins of introduced material culture will reflect its East, South, and Southeast Asian and, ultimately, global connectivity. [ABSTRACT FROM AUTHOR]

The current air cargo loading plan handles the Air Cargo Palletization Problem (ACPP) and the Aircraft Weight and Balance Problem (WBP) separately, which has an impact on the optimization of the payload and the aircraft's center of gravity (CG). Thanks to improvements in computer processing power, the joint combinatorial optimization of ACPP and WBP is now feasible. Three integer linear programming models are proposed: a Bi-objective Optimization Model (BOM), a Combinatorial Optimization Model (COM), and an Improved Combinatorial Optimization Model (IOM). The objectives of the models are the maximum loading capacity and the lowest CG deviation from a specified target CG. The models also consider a wide range of restrictions in the actual packing and stowage procedures, such as volume, weight, loading position, aircraft balance, and other aspects of aircraft and unit load devices. Four scenarios with various conditional metrics for three models are solved for the B777F aircraft using Gurobi. The results of the computations demonstrate that the BOM has the fastest solution speed, but the CG deviation is the largest, and in several cases the CG deviation results are unacceptable. The COM has the longest solution time, which is difficult to tolerate in practice. Despite taking a little longer to solve computationally than the BOM, the IOM offers the best optimization solution. [ABSTRACT FROM AUTHOR]

Consider a storage area where arriving items are stored temporarily in bounded capacity stacks until their departure. We look into the problem of deciding where to put an arriving item with the objective of minimizing the maximum number of stacks used over time. The decision has to be made as soon as an item arrives, and we assume that we only have information on the departure times for the arriving item and the items currently at the storage area. We are only allowed to put an item on top of another item if the item below departs at a later time. We refer to this problem as online stacking. We assume that the storage time intervals are picked i.i.d. from [ 0 , 1 ] × [ 0 , 1 ] using an unknown distribution with a bounded probability density function. Under this mild condition, we present a simple polynomial time online algorithm and show that the competitive ratio converges to 1 in probability. The result holds if the stack capacity is o (n) , where n is the number of items, including the realistic case where the capacity is a constant. Our experiments show that our results also have practical relevance. [ABSTRACT FROM AUTHOR]

Train stowage planning problem of steel coil (TSPP) is to determine loading locations of the coils on train railcars, which is rarely studied, and an important optimisation problem in real iron and steel industry. In this paper, first, according to the actual situations of a steel products transportation department, the problem is formulated as an integer programming (IP) mathematical model in which multiple destination stations, varied stowing modes and different railcar types are considered. Then, on the basis of a general discrete optimisation algorithm framework, i.e. pointer-based discrete differential evolution (PDDE), a novel variant (T-PDDE) is proposed for effectively solving the TSPP. In particular, to deal with the issue of transformation between stowage plan and algorithm individual, a problem-based coding method is designed. To further enhance the algorithm performance, a double levels evolution strategy and an opposite-based local search are developed based on the features of problem. Finally, with the practical and simulative data, extensive comparison experiments are carried out to evaluate the proposed algorithm. The numerical results demonstrate the superiority of T-PDDE on solving TSPP. [ABSTRACT FROM AUTHOR]

The stowage decision determines how arriving products are distributed in a storage system or warehouse. In particular, we consider the zone-stowage decision for large warehouses that are organised into distinct storage zones. An example would be a multi-floor warehouse where each floor is a storage zone. Each storage zone has limited picking capacity; we want to stow the product inventory across the storage zones so as to be able to meet uncertain demand requirements with the limited picking capacity in each zone. Determining how to spread the inventory across the storage zones is the zone-stowage decision that we consider in this paper. With a simulation study, we identify two zone-stowage policies that are effective in balancing the picking workload across different storage zones. The first zone-stowage policy achieves a chaining-inspired allocation by splitting the received quantity for each product across two storage zones; the second zone-stowage policy explicitly tracks the expected workload for each storage zone, termed the velocity of the zone, and then stows arriving products to the storage zone with the smallest velocity. [ABSTRACT FROM AUTHOR]

The aircraft weight and balance problem (WBP) defined in terms of selecting unit load devices (ULDs) from an available set and allocating them to specified positions in cargo holds. It is critical to aircraft safety as well as operational efficiency and profit. It is an NP‐hard problem combining characteristics of the knapsack problem and generalized assignment problems, as well as complex practical constraints. A mixed integer programming model is constructed to maximize the total payload and minimize the center of gravity (CG) deviation by considering the constraints of positions, weights, balance etc. In contrast to prior studies using a constant delta to limit CG deviation, a new set of CG envelope constraints is proposed based on the variation in actual CG under different statuses and precise describing CG. A linearizing strategy is further designed to simplify the nonlinear CG envelope constraints. The proposed model can be solved using commercial optimization software within a few seconds and maintain the CG within the designated CG envelope in all test instances; in contrast, the other (CG deviation‐based) method may result in flight hazards in some scenarios. [ABSTRACT FROM AUTHOR]

In the port terminals of Peru, the placement of fishery products such as frozen fish within refrigerated containers is done manually with the help of gaff hooks. The workers are organized into groups according to their experiences and knowledge in order to meet the production goals, following the quality and safety standards indicated by the organization. The introduction of technologies in the process of cargo stowage did not meet the expected results on reducing the long-term physical effects on operational personnel, who are the ones with the knowledge for the processes, which represents a disregard of the experience and loss of money in technology that is wrongly used by the workers. The challenge of this ergonomic intervention is to analyze the process of cargo stowage of frozen fish under a systematic approach to understand the ways and factors of this job, while getting the workers involved.

This paper considers a generalized version of the planar storage location problem arising in the stowage planning for Roll-on/Roll-off ships. A ship is set to sail along a predefined voyage where given cargoes are to be transported between different port pairs along the voyage. We aim at determining the optimal stowage plan for the vehicles stored on a deck of the ship so that the time spent moving vehicles to enable loading or unloading of other vehicles (shifting), is minimized. We propose a novel mixed integer programming model for the problem, considering both the stowage and shifting aspect of the problem. An adaptive large neighborhood search (ALNS) heuristic with several new destroy and repair operators is developed. We further show how the shifting cost can be effectively evaluated using Dijkstra's algorithm by transforming the stowage plan into a network graph. The computational results show that the ALNS heuristic provides high quality solutions to realistic test instances. [ABSTRACT FROM AUTHOR]

In order to complete the loading operation in a short time, the genetic algorithm was improved, and the improved mechanisms such as the total crossover of the population and the distributed dynamic penalty function method were proposed. The distribution of ballast water in barge stowage was optimized. The calculation of the ship's floating state, stability, the check of the program strength, and the improvement of the genetic algorithm were discussed. By simplifying the model, all ballast water tanks were involved in the stowage, so as to better meet the limitation of tide level, tank capacity and strength. A more adaptable load optimization solution was obtained. The results show that the improved genetic algorithm has shorter time and higher efficiency than the basic loading scheme. The improved genetic algorithm was used to optimize the barge loading plan, which met the engineering requirements and shorten the working time of the barge. Therefore, the research on the improved genetic algorithm can effectively improve the quality and reliability of the project, which is beneficial to improve the scientific, safety and reliability of the barge loading operation. This program has important implications for marine engineering. [ABSTRACT FROM AUTHOR]

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• We study the stowage problem in inland shipping. • We develop two novel mathematical model. • A hybrid optimization framework is developed. • The metaheuristic produces high-quality results against the relaxed model. • Experiments on real-world data shows the limitations of current practices. 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. [ABSTRACT FROM AUTHOR]

In this paper, we present a method for finding high quality solutions for the Blocks Relocation Problem with Stowage Plan (BRLP). The interest for this problem comes from the fact that previous research has shown that a significant amount of savings can be achieved, if the process of specifying the loading sequence takes into account both the state of the bay and the stowage plan. In this work, we propose a two step greedy algorithm for the BRLP. In the first one, a heuristic is used to select the next container to be loaded into the vessel. In the second step, a new heuristic is used to relocate obstructing containers. The solutions acquired in this way are improved using a correction procedure. The idea of the correction procedure is to use a heuristic approach to recognize undesirable properties of a solution and remove them. Finally, the method is extended towards the GRASP metaheuristic. Our computational experiments show that the proposed approach manages to significantly outperform existing methods for the BRLP. [ABSTRACT FROM AUTHOR]

The Cargo Mix Problem (CMP) chooses and distributes types of containers to load into bay subsections of a container vessel. In this paper, we extend existing Mixed Integer Programming models for the CMP by considering containers with dangerous goods. We show that our model can be optimally solved in reasonable time using standard software. [ABSTRACT FROM AUTHOR]

In the port terminals of Peru, the placement of fishery products such as frozen fish within refrigerated containers is done manually with the help of gaff hooks. The workers are organized into groups according to their experiences and knowledge in order to meet the production goals, following the quality and safety standards indicated by the organization. The introduction of technologies in the process of cargo stowage did not meet the expected results on reducing the long-term physical effects on operational personnel, who are the ones with the knowledge for the processes, which represents a disregard of the experience and loss of money in technology that is wrongly used by the workers. The challenge of this ergonomic intervention is to analyze the process of cargo stowage of frozen fish under a systematic approach to understand the ways and factors of this job, while getting the workers involved. [ABSTRACT FROM AUTHOR]

In transportation of goods in large container ships, shipping industries need to minimize the time spent at ports to load/unload containers. An optimal stowage of containers on board minimizes unnecessary unloading/reloading movements, while satisfying many operational constraints. We address the basic container stowage planning problem (CSPP). Different heuristics and formulations have been proposed for the CSPP, but finding an optimal stowage plan remains an open problem even for small-sized instances. We introduce a novel formulation that decomposes CSPPs into two sets of decision variables: the first defining how single container stacks evolve over time and the second modeling port-dependent constraints. Its linear relaxation is solved through stabilized column generation and with different heuristic and exact pricing algorithms. The lower bound achieved is then used to find an optimal stowage plan by solving a mixed-integer programming model. The proposed solution method outperforms the methods from the literature and can solve to optimality instances with up to 10 ports and 5,000 containers in a few minutes of computing time. The online appendix is available at https://doi.org/10.1287/trsc.2017.0795. [ABSTRACT FROM AUTHOR]

Zhao, N.; Guo, Y.; Xiang, T.; Xia, M.; Shen, Y., and Mi, C., 2018. Container ship stowage based on monte carlo tree search. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 540–547. Coconut Creek (Florida), ISSN 0749-0208. With the development of larger ships, modernized wharves, standardized production, meticulous management, and flexible service in container transportation, port production management is becoming increasingly intelligent. How to improve the efficiency when making stowage plans, the core issue in container terminals, has become a popular topic in research. Starting with the stowage issue, this paper provides rational solutions to stowage location and loading sequence of unloaded containers on the yard, giving overall consideration on ship owners' requirement and dock authority's practical operation. Considering turnover on yard, RTG cross-container operation and RTG shifting, based on loading principles and constraints, this paper establishes an optimized model for multiple targets and creates an MCTS method, where five procedures including extension and option, together with corresponding strategies, are designed according to the search tree. Practical numerical examples indicate that the suggested model and algorithm can produce effective solution in due time. This is the first time that MCTS is applied for loading issues in container terminals, so this paper does not only use and perfect theories on optimizing, system analysis and decision, but also contribute to the intelligentization of container terminals. Relevant methods and thinking are referential and applicable to the study of issues of the same kind. [ABSTRACT FROM AUTHOR]

The operational efficiency of a port depends on proper container movement planning, called “stowage planning”, especially because unloading and loading container ships demands time, and this has a cost. Thus, the optimization of operations through stages is important to avoid blockage activities. This paper proposes a framework for solving the 3D stowage planning (3D SP) problem for container ships integrated with the scheduling of quay cranes (SQC) problem. 3D SP and SQC problems are interrelated and combinatorial, justifying the applications of meta-heuristics like a genetic algorithm combined with simulation and representation by rules. The robustness of the developed approach is attested in problems with 30 ports, 1500 TEUs ship or 15 ports and 22,000 TEUs ship and two quay cranes. These studies showed that the addition of the SQC problem leads to a 45.82% increase in load/unload time for the 3D SP problem solution, on average. This could help the charterer to avoid paying charges to the shipowner due to its an extra unplanned use of the vessel. Additionally, the developed methodology also helps to explain a long term phenomena of continuous increasing in container ship capacity since 1950s. [ABSTRACT FROM AUTHOR]

This paper studies the problem of stowage planning within a vessel bay in a multiple port transportation route, aiming at minimizing the total container shifting fee. Since the access to containers is in the top-to-bottom order for each stack, reshuffle operations occur when a target container to be unloaded at its destination port is not stowed on the top of a stack at the time. Each container shift via a quay crane induces one unit of shifting fee that depends on the charge policy of the local container port. Previous studies assume that each container shift consumes a uniform cost in all ports and thus focus on minimizing the total number of shifts or the turnaround time of the vessel. Motivated by the observation that different ports are of nonuniform fee for each container shift, we propose a mixed integer programming (MIP) model for the problem to produce an optimal stowage planning with minimum total shifting fee in this work. Moreover, as the considered problem is NP-hard due to the NP-hardness of its counterpart with uniform unit shifting fee, we propose an improved genetic algorithm to solve the problem. The efficiency of the proposed algorithm is demonstrated via numerical experiments. [ABSTRACT FROM AUTHOR]

Ship stowage plan is the management connection of quae crane scheduling and yard crane scheduling. The quality of ship stowage plan affects the productivity greatly. Previous studies mainly focuses on solving stowage planning problem with online searching algorithm, efficiency of which is significantly affected by case size. In this study, a Deep Q-Learning Network (DQN) is proposed to solve ship stowage planning problem. With DQN, massive calculation and training is done in pre-training stage, while in application stage stowage plan can be made in seconds. To formulate network input, decision factors are analyzed to compose feature vector of stowage plan. States subject to constraints, available action and reward function of Q-value are designed. With these information and design, an 8-layer DQN is formulated with an evaluation function of mean square error is composed to learn stowage planning. At the end of this study, several production cases are solved with proposed DQN to validate the effectiveness and generalization ability. Result shows a good availability of DQN to solve ship stowage planning problem. [ABSTRACT FROM AUTHOR]

This paper considers a real operational problem of routing and scheduling a fleet of fuel supply vessels used to service customer ships anchored outside a major port. The problem can be formulated as a rich multi-trip vehicle routing problem, including constraints related to stowage and time-dependent sailing times. An arc-flow and a path-flow model are developed and compared. A computational study shows that the path-flow model is superior and can be used in real planning situations. We also discuss how the model can be used in a real-time setting when new orders arrive and deviations from the plan occur. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of determining stowage plans for containers into ships having to visit a given number of ports in their circular route. The problem is denoted Multi-Port Master Bay Plan Problem (MP-MBPP). In practice, the MP-MBPP consists in determining how to stow a given set of containers, split into different groups, according to their size, type, class of weight and destination, into bay locations, either on the deck or in the stow. Some structural and operational constraints, related to the containers, the ship and the maritime terminals, have to be satisfied. The single port MBPP is a NP-hard optimization problem, and has been proposed in the literature from 2001. From then, some variants of the problem have been presented, together with the related solution methods, mainly aimed at including in the corresponding models realistic features, required as a consequence of the naval gigantism. As a novel issue, in the present work, we look for stowage plans where the set of containers to be loaded on board at each port of the route consists of standard, reefer and open top ones. Hatches positions in the ships are considered too. We present a new mixed integer programming (MIP) model for the MP-MBPP able to manage realistic scenarios and find stowage plans for containerships up to 18,000 TEUs. The model is finalized to be solved with a commercial MIP solver. The reported computational experimentation shows that the model is very efficient and could be fruitfully used for facing real-size instances of the problem. [ABSTRACT FROM AUTHOR]