A beam search algorithm for the load sequencing of outbound containers in port container terminals

OR Spectrum ◽  
2004 ◽  
Vol 26 (1) ◽  
pp. 93-116 ◽  
Author(s):  
Kap Hwan Kim ◽  
Jin Soo Kang ◽  
Kwang Ryel Ryu
Keyword(s):  
Search Algorithm ◽  
Container Terminals ◽  
Beam Search ◽  
Outbound Containers

Priority-based speed control strategy for automated guided vehicle path planning in automated container terminals

2020 ◽  
Vol 42 (16) ◽  
pp. 3079-3090 ◽  
Author(s):  
Meisu Zhong ◽  
Yongsheng Yang ◽  
Shu Sun ◽  
Yamin Zhou ◽  
Octavian Postolache ◽  
...  
Keyword(s):  
Path Planning ◽  
Control Strategy ◽  
Search Algorithm ◽  
Waiting Times ◽  
Optimal Path ◽  
Speed Control ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Operating Efficiency ◽  
Continuous Increase

With the continuous increase in labour costs and the demands of the supply chain, improving the efficiency of automated container terminals has been a key factor in the development of ports. Automated guided vehicles (AGVs) are the main means of horizontal transport in such terminals, and problems in relation to their use such as vehicle conflict, congestion and waiting times have become very serious, greatly reducing the operating efficiency of the terminals. In this article, we model the minimum driving distance of AGVs that transport containers between quay cranes (QCs) and yard cranes (YCs). AGVs are able to choose the optimal path from pre-planned paths by testing the overlap rate and the conflict time. To achieve conflict-free AGV path planning, a priority-based speed control strategy is used in conjunction with the Dijkstra depth-first search algorithm to solve the model. The simulation experiments show that this model can effectively reduce the probability of AGVs coming into conflict, reduce the time QCs and YCs have to wait for their next task and improve the operational efficiency of AGV horizontal transportation in automated container terminals.

scholarly journals Research on Cooperative Scheduling of Automated Quayside Cranes and Automatic Guided Vehicles in Automated Container Terminal

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Qianru Zhao ◽  
Shouwen Ji ◽  
Dong Guo ◽  
Xuemin Du ◽  
Hongxuan Wang
Keyword(s):  
Search Algorithm ◽  
Container Terminal ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Total Energy Consumption ◽  
Two Stage ◽  
Taboo Search ◽  
Automatic Guided Vehicles ◽  
Collaborative Scheduling ◽  
Taboo Search Algorithm

According to previous research studies, automated quayside cranes (AQCs) and automated guided vehicles (AGVs) in automated container terminals have a high potential synergy. In this paper, a collaborative scheduling model for AQCs and AGVs is established and the capacity limitation of the transfer platform on AQCs is considered in the model. The minimum total energy consumption of automated quayside cranes (AQCs) and Automatic Guided Vehicles (AGVs) is taken as the objective function. A two-stage taboo search algorithm is adopted to solve the problem of collaborative scheduling optimization. This algorithm integrates AQC scheduling and AGV scheduling. The optimal solution to the model is obtained by feedback from the two-stage taboo search process. Finally, the Qingdao Port is taken as an example of a data experiment. Ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the two-stage taboo search algorithm since it can find near-optimal solutions, precisely and accurately.

scholarly journals Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4115
Author(s):  
Jolanta Koszelew ◽  
Joanna Karbowska-Chilinska ◽  
Krzysztof Ostrowski ◽  
Piotr Kuczyński ◽  
Eric Kulbiej ◽  
...  
Keyword(s):  
Trajectory Planning ◽  
Search Algorithm ◽  
Simulated Data ◽  
General Idea ◽  
Automatic Identification ◽  
Identification System ◽  
Beam Search ◽  
Autonomous Surface Vehicles ◽  
Open Sea ◽  
Collision Trajectory

A single anti-collision trajectory generation problem for an “own” vessel only is significantly different from the challenge of generating a whole set of safe trajectories for multi-surface vehicle encounter situations in the open sea. Effective solutions for such problems are needed these days, as we are entering the era of autonomous ships. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations. The proposed original multi-surface vehicle beam search algorithm (MBSA), based on the beam search strategy, solves the problem. The general idea of the MBSA involves the application of a solution for one-to-many encounter situations (using the beam search algorithm, BSA), which was tested on real automated radar plotting aid (ARPA) and automatic identification system (AIS) data. The test results for the MBSA were from simulated data, which are discussed in the final part. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations involving moving autonomous surface vehicles, excluding Collision Regulations (COLREGs) and vehicle dynamics.

A beam search algorithm for the circular packing problem

2009 ◽  
Vol 36 (5) ◽  
pp. 1513-1528 ◽  
Author(s):  
Hakim Akeb ◽  
Mhand Hifi ◽  
Rym M’Hallah
Keyword(s):  
Search Algorithm ◽  
Packing Problem ◽  
Beam Search ◽  
Circular Packing
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