Container Ship Stowage Research Articles

On improving containership stowage planning from the perspective of an entire voyage

On improving containership stowage planning from the perspective of an entire voyage

Storage strategy of outbound containers with uncertain weight by data-driven hybrid genetic simulated annealing algorithm.

It is necessary to ensure the ship's stability in container ship stowage and loading and unloading containers. This work aims to reduce the container dumping operation at the midway port and improve the efficiency of ship transportation. Firstly, the constraint problem of the traditional container ship stacking is introduced to realize the multi-condition mathematical model of the container ship, container, and wharf. Secondly, a Hybrid Genetic and Simulated Annealing Algorithm (HGSAA) model is proposed for the container stacking and loading stacking in the yard. The specific container space allocation and multi-yard crane adjustment scheme are studied. Finally, the effectiveness of the multi-condition container ship stowage model is verified by numerical experiments by changing the number of outbound containers, storage strategies, storage yards, and bridges. The experimental results show that the HGSAA mode converges to 106.1min at the 751st iteration. Of these, the non-loading and unloading time of yard bridge 1 is 3.43min. The number of operating boxes is 25. The non-loading and unloading time of yard bridge 2 is 3.2min, and the operating box volume is 25 boxes. The objective function of the genetic algorithm converges when it iterates to generation 903 and 107.9min. Among them, the non-loading and unloading time of yard bridge 1 is 4.1min. The non-loading and unloading time of yard bridge 2 is 3.1min. Therefore, the proposed HGSAA has a faster convergence speed than the genetic algorithm and can obtain relatively good results. The proposed container stacking strategy can effectively solve the specific container allocation and multi-yard crane scheduling problems. The finding provides a reference for optimizing container scheduling and improving shipping transportation efficiency.

Integrated Containership Stowage Planning: A Methodology for Coordinating Containership Stowage Plan and Terminal Yard Operations

This study aims at achieving the optimized stowage plan based on the containers’ distribution in the yard and space structure of the ship by integrating the containership stowage problem with the block relocation and loading problem. The containership’s physical structure contributes to a variety of stowage plans, and the containers’ distribution in the yard restrains the container loading sequence. The integrated containership stowage model is established, considering irregular format ship configuration, the weight of each individual container and the stability constraints by limiting the range of related indicators to strengthen real-world scalability. Commercial managers can solve small-scale instances to reduce handling moves in the terminal yard by using the mathematical model, but they cannot solve large-scale instances in the real world. Thus, this study presents a heuristic algorithm to coordinate containership stowage and terminal yard operations. Numerical experiments compare the optimal solutions using the heuristic algorithm to that by CPLEX and GUROBI in small-scale instances, and the respective results are displayed in two stages using the heuristic algorithm. Computational results show that the proposed algorithm can provide the industry with decision support by dramatically and quickly reducing the relocations in the yard and the shifts in the containership, helping the container terminal keep a sustainable development process.

An agent-based approach to simulate the containership stowage problem

An agent-based approach to simulate the containership stowage problem

Many-Objective Container Stowage Optimization Based on Improved NSGA-III

The container ship stowage planning problem (CSPP) is a very complex and challenging issue concerning the interests of shipping companies and ports. This article has developed a many-objective CSPP solution that optimizes ship stability and reduces the number of shifts over the whole route while at the same time considering realistic constraints such as the physical structure of the ship and the layout of the container yard. Use the initial metacentric height (GM) along with the ship’s heeling angle and trim to measure its stability. Meanwhile, use the total amount of relocation in the container terminal yard, the voluntary shift in the container ship’s bay, and the necessary shift of the future unloading port to measure the number of shifts on the whole route. This article proposes a variant of the nondominated sorting genetic algorithm III (NSGA-III) combined with local search components to solve this problem. The algorithm can produce a set of non-dominated solutions, then decision-makers can choose the best practical implementation based on their experience and preferences. After carrying out a large number of experiments on 48 examples, our calculation results show that the algorithm is effective compared with NSGA-II and random weighted genetic algorithms, especially when applied to solve many-objective CSPPs.

Research on Intelligent Loading System for Container Ships

Container transportation is an important part of the global transportation industry, and its transport capacity affects the development of the global economy to a certain extent. Ship stowage is an important part of container transportation. Its intellectualization level determines the time of container ships in port and the frequency of overturning containers, thus affecting the efficiency and economic benefits of ship transportation. Based on the container ship stowage process, this paper analyzed the factors affecting the stowage, focused on the study of the composition of intelligent stowage system, and provided a safe and reliable idea for the construction of container ship stowage system.

Integer Linear Programming Models for the Containership Stowage Problem

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.

Solving inland container ship stowage planning problem on full route through a two-phase approach

Inland container ship emphasises capacity utilisation due to its limited capacity. Its stability is very sensitive to the stowage plan. The shipping line planners are under pressure to make efficient stowage plan on full route. This paper adopts a two-phase approach to separate the problem into two planning levels: multi-port master bay plan problem (MP-MBPP) on full route and slot plan problem (SPP) for each bay at each port. The mathematical models are proposed respectively for both sub-problems based on mixed integer programming. For each sub-problem, the greedy randomised adaptive search procedure (GRASP) and the heuristic evolutionary strategy (HES) algorithm are proposed, respectively. The grey entropy parallel analysis (GEPA) method is presented to guide HES in multi-objective optimisation. Experimental results based on real-world scenarios are presented to show the efficacy of proposed algorithms and method.

Solving inland container ship stowage planning problem on full route through a two-phase approach

Inland container ship emphasises capacity utilisation due to its limited capacity. Its stability is very sensitive to the stowage plan. The shipping line planners are under pressure to make efficient stowage plan on full route. This paper adopts a two-phase approach to separate the problem into two planning levels: multi-port master bay plan problem (MP-MBPP) on full route and slot plan problem (SPP) for each bay at each port. The mathematical models are proposed respectively for both sub-problems based on mixed integer programming. For each sub-problem, the greedy randomised adaptive search procedure (GRASP) and the heuristic evolutionary strategy (HES) algorithm are proposed, respectively. The grey entropy parallel analysis (GEPA) method is presented to guide HES in multi-objective optimisation. Experimental results based on real-world scenarios are presented to show the efficacy of proposed algorithms and method.

Optimizing the Stowage Planning and Block Relocation Problem in Inland Container Shipping

The stowage planning and block relocation problem (SPBRP) consider the relations between stowage planning and block relocation comprehensively, in which the retrieval sequence of containers in yard and the stowage plan of a ship are concerned. In this paper, an integer programming formulation called SPBRP-I is presented for the proposed problem in inland container liner shipping to minimize the total number of relocations in yard and re-handles in ship. To deal with the utilization preference in inland shipping, the minimization of ship stack occupancy number is introduced into SPBRP-I to develop a new model called SPBRP-II. In view of the complexity of problem-solving, a heuristic algorithm (HA) based on priority sorting, retrieval and local search strategies is proposed to achieve the efficient optimization. The algorithm consists of three parts including the yard container retrieving, yard container relocation and ship stowage planning. Finally, the container liner shipping on the Yangtze River is chosen with some typical ships for the case study. Numerical results show that SPBRP-II performs better than the original SPBRP-I, and it's more suitable for solving the small-sized cases. Compared with the models, the algorithm with retrieval strategy RS1 (HA_RS1) can achieve the efficient problem solving with high-quantity solutions and very short computational time.

Container Ship Stowage Based on Monte Carlo Tree Search

ABSTRACT 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 loadi...

Solution Strategies for a Multiport Container Ship Stowage Problem

The multiport container ship stowage problem consists in determining the position of the containers on board a ship along its route with the objective of minimizing the number of unproductive moves required in the loading and unloading operations at each port. This paper presents an integer programming model for the problem and proposes several sets of valid constraints that bring its LP‐relaxation closer to an integer solution. Moreover, it presents a GRASP algorithm that generates stowage plans with a minimal number of unproductive moves in a high percentage of medium and large‐size instances. An extended computational analysis has been performed in which, to the best of the authors’ knowledge, the efficiency of integer programming models for the problem is tested for the first time. With respect to GRASP, the computational results show that it performs well on different sized datasets.

Applying expert knowledge to containership stowage planning: an empirical study

Several maritime accidents have been caused recently by inappropriate stowage planning of cargo ships, specifically large containerships. This study focuses on improving stowage planning to increase navigational safety. Whereas most previous studies have only considered the position of containers in a ship, the stowage planning developed here considers container positions both onboard and at the terminal. The role of navigational safety requirements—such as metacentric height, trim, heel, bending moment, torsional moment, draft and adherence to International Maritime Dangerous Goods code—code has also been largely absent from previous studies. Therefore, our study proposes stowage planning methods that meet the above safety requirements. An empirical stowage planning study, applied to five containerships of an international shipping company, is presented. The five cases illustrate the effectiveness of the stowage planning methods developed in this paper.

Group-Bay Stowage Planning Problem for Container Ship

Abstract Stowage planning is the core of ship planning. It directly influences the seaworthiness of container ship and the handling efficiency of container terminal. As the latter step of container ship stowage plan, terminal stowage planning optimizes terminal cost according to pre-plan. Group-Bay stowage planning is the smallest sub problem of terminal stowage planning problem. A group-bay stowage planning model is formulated to minimize relocation, crane movement and target weight gap satisfying both ship owner and container terminal. A GA-A* hybrid algorithm is designed to solve this problem. Numerical experiment shown the validity and the efficiency.

Symbolic Configuration for Interactive Container Ship Stowage Planning

Low‐cost containerized shipping requires high‐quality stowage plans. Scalable stowage planning optimization algorithms have been developed recently. All of these algorithms, however, produce monolithic solutions that are hard for stowage coordinators to modify, which is necessary in practice owing to exceptions and operational disruptions. This article introduces an approach for modifying a stowage plan interactively without breaking its constraints. We focus on rearranging the containers in a single‐bay section and show two approaches for providing complete and backtrack‐free decision support using symbolic configuration techniques, one based on binary decision diagrams and one based on DPLL solvers. We show that binary decision diagrams can be used to solve real‐world sized instances of a single bay, and that search‐based solvers can be used to solve simplified instances going beyond a single bay.

On the complexity of container stowage planning problems

The optimization of container ship and depot operations embeds the k-shift problem, in which containers must be stowed in stacks such that at most k containers must be removed in order to reach containers below them. We first solve an open problem introduced by Avriel et al. (2000) by showing that changing from uncapacitated to capacitated stacks reduces the complexity of this problem from NP-complete to polynomial. We then examine the complexity of the current state-of-the-art abstraction of container ship stowage planning, wherein containers and slots are grouped together. To do this, we define the hatch overstow problem, in which a set of containers are placed on top of the hatches of a container ship such that the number of containers that are stowed on hatches that must be accessed is minimized. We show that this problem is NP-complete by a reduction from the set-covering problem, which means that even abstract formulation of container ship stowage planning is intractable.

A Heuristic Approach for the Containership Stowage Problem in Multiple Port-of-call Route

A Heuristic Approach for the Containership Stowage Problem in Multiple Port-of-call Route

Review of containership stowage plans for full routes

Containership stowage plans are a pivotal teaches in the system of container transportation. With the increasing containers shipping, planning containership stowage has become more and more complicated. So intelligent stowage planning for containerships is of great significance. An effective stowage plan may improve efficiency of transportation system. First, the progress of containership stowage plan at home and abroad is reviewed, including the latest developments, such as the application of various optimization methods and computer techniques to the problem. Then, the complexities of the problem are discussed and areas where investigations are still needed are pointed out. This will provide a reference for further research on the subject.

An Investigation into Effectiveness of Container Arrangements on Optimizing a Containership Stowage Plan

An Investigation into Effectiveness of Container Arrangements on Optimizing a Containership Stowage Plan

A 3D-BPP approach for optimising stowage plans and terminal productivity

This paper addresses the problem of determining stowage plans for containers in a ship, that is the so-called master bay plan problem (MBPP). MBPP is NP-complete [Botter, R.C., Brinati, M.A., 1992. Stowage container planning: A model for getting an optimal solution. IFIP Transactions B (Applications in Technology) B-5, 217–229; Avriel, M., Penn, M., Shpirer, N., 2000. Container ship stowage problem: Complexity and connection to the colouring of circle graphs. Discrete Applied Mathematics 103, 271–279]. We present a heuristic method for solving MBPP based on its relation with the three-dimensional bin packing problem (3D-BPP), where items are containers and the only bin is the ship. We look for stowage plans that take into a proper account structural and operational constraints, related to both the containers and the ship, and maximise some important terminal performance indexes, such as the effective and mean net crane productivity. Our aim is to evaluate how stowage plans can influence the performance of the quay. A validation of the proposed approach with some test cases related to containership docks at the port of Genoa (Italy) is given. The results of real instances of the problem and the comparison with a validated heuristic for MBPP, show the effectiveness of the proposed approach in producing stowage plans that minimise the total loading time and allow an efficient use of the quay equipment.