Mathematical formulation and heuristic algorithm for the block relocation and loading problem

Zhu, Huiling; Ji, Mingjun; Guo, Weiqi; Wang, Qingbin; Yang, Yongzhi

doi:10.1002/nav.21843

Cited by 11 publications

(4 citation statements)

References 44 publications

(62 reference statements)

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“…Equation ( 4) expresses that each container can only be stacked in one sub-block. Constraint (5) indicates that the number of sub-blocks assigned to a vessel can not exceed the permitted quantities. Constraint (6) requires that the quantities of export containers stacked in the sub-block k during period p should not exceed the allowed quantities of containers.…”

Section: Model Establishmentmentioning

confidence: 99%

“…According to United Nations Conference on Trade and Development (2020), the world container terminal throughput in 2019 rises by 1.88% to 0.81 billion Twenty-foot Equivalent Units (TEUs) from 0.796 billion TEUs in 2018. With the rapid growth in throughput, terminal operators have begun to pay more attention to the improvement of container terminal efficiency [5][6][7] . When the terminal efficiency is gradually improved, it can meet the increasing demand of the terminal and ensure the improvement of the terminal economic benefits.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Period Coordinated Optimization on Berth Allocation and Yard Assignment in Container Terminals Based on Truck Route

Guo

Zhu

2021

IEEE Access

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Berths and yards are the most critical parts of container terminals. Their efficiency directly influences the terminal operation efficiency. The multi-period coordinated optimization on berth allocation and yard assignment has been studied considering a multi-period interaction between the berth and yard. The coordinated optimization problem is formulated as an integer programming, aimed at minimizing the total truck travel distance, where the decision variables are the berthing positions for visiting vessels and the storage positions for export containers. In this work, the complexity of this problem is theoretically demonstrated. A tabu genetic algorithm is designed to solve the problem to obtain the optimal berthing and export container stacking positions. With this algorithm, the rule is applied to generate the initial feasible solutions, and crossover and mutation operations are simultaneously applied to optimize the initial solutions. Finally, two different scenarios, the determinate berth allocation scenario and the determinate yard assignment scenario, are presented to compare the influence of berth allocation and yard assignment on truck travel distance. The numerical experiments demonstrate that the berthing positions, stacking positions and the period segments directly affect the truck travel distance. And the multi-period coordinated optimization problem can effectively shorten the truck travel distance and improve the efficiency of the terminal operation, which supports the decisions of terminal operators and maintains the efficient development of the terminal.INDEX TERMS export container, berth allocation, yard assignment, multi-period optimization, coordinated allocation, tabu genetic algorithm.

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Section: Model Establishmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Period Coordinated Optimization on Berth Allocation and Yard Assignment in Container Terminals Based on Truck Route

Guo

Zhu

2021

IEEE Access

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“…Many algorithms to solve bin allocation exist, such as the heuristic algorithm [6], [12] particle swarm algorithm [13], tabu search algorithm [14], mixed harmony simulated annealing algorithm [10], [15], and genetic algorithm [9], [16], [17]. Among these, the genetic algorithm is used more widely used.…”

Section: Introductionmentioning

confidence: 99%

Dangerous Goods Container Location Allocation Strategy based on Improved NSGA-II Algorithm

Zhang¹,

Liang²,

Chen³

2022

IJACSA

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The characteristics of port dangerous goods are complicated and diverse in danger, which is very likely to cause chain effects once a fire and explosion accident occurs. Based on the distribution characteristics of dangerous goods container yards and the special national storage requirements for dangerous goods containers, the paper establishes a multiobjective optimization model with a double priority of safety and economy, starting from reducing the number of reversals. The improved non-dominated sorting genetic algorithm based on the elite strategy was used to solve the model and the algorithm was tested and improved. Based on the Pareto optimal solution set, the entropy weight-TOPSIS method was used to optimize the sorting of multiple solution sets, which improved the performance of the algorithm. The analysis further clarifies the important relationship between attributes, and the running time is shortened by 85.7% compared with the traditional NSGA algorithm. The optimization model and algorithm can provide decision support for the actual operation and management of container storage, and provide a good reference for accident risk prevention and control.

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“…In recent years, some scholars have begun to pay attention to the relationship between the containership stowage plan and the yard operation plan. Focusing on the loading operation process of a single ship bay, Zhu et al [30] defined the block relocation and loading problem (BRLP) in detail and established an integer linear programming model. Considering that the BRLP is a special case of the BRP, a rule-based heuristic algorithm that can be commonly used to solve the BRLP and BRP is designed.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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

Zhu

2022

Sustainability

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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.

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Mathematical formulation and heuristic algorithm for the block relocation and loading problem

Cited by 11 publications

References 44 publications

Multi-Period Coordinated Optimization on Berth Allocation and Yard Assignment in Container Terminals Based on Truck Route

Multi-Period Coordinated Optimization on Berth Allocation and Yard Assignment in Container Terminals Based on Truck Route

Dangerous Goods Container Location Allocation Strategy based on Improved NSGA-II Algorithm

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

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