Receding horizon path planning of automated guided vehicles using a time‐space network model

2020 ◽  
Vol 41 (6) ◽  
pp. 1889-1903 ◽  
Author(s):  
Jianbin Xin ◽  
Liuqian Wei ◽  
Dongshu Wang ◽  
Hua Xuan
Keyword(s):  
Path Planning ◽  
Network Model ◽  
Automated Guided Vehicles ◽  
Receding Horizon ◽  
Space Network ◽  
Time Space

scholarly journals A Time-Space Network Model for Collision-Free Routing of Planar Motions in a Multirobot Station

2020 ◽  
Vol 16 (10) ◽  
pp. 6413-6422 ◽  
Author(s):  
Jianbin Xin ◽  
Chuang Meng ◽  
Frederik Schulte ◽  
Jinzhu Peng ◽  
Yanhong Liu ◽  
...  
Keyword(s):  
Network Model ◽  
Space Network ◽  
Time Space ◽  
Planar Motions

scholarly journals Routing of a Multi-Robot System Using a Time-Space Network Model

2019 ◽  
Author(s):  
Chuang Meng ◽  
Jianbin Xin ◽  
Jinzhu Peng ◽  
Rudy R. Negenborn
Keyword(s):  
Network Model ◽  
Robot System ◽  
Space Network ◽  
Time Space ◽  
Multi Robot

scholarly journals A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 780 ◽  
Author(s):  
Zihan Qu ◽  
Shiwei He
Keyword(s):  
Network Model ◽  
Traffic Congestion ◽  
Flow Distribution ◽  
Distribution Model ◽  
A Algorithm ◽  
Traffic Forecasting ◽  
Space Network ◽  
Model Based ◽  
Time Space ◽  
Feasible Path

Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time-space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency. Based on the train diagram, we constructed a symmetric time-space network for the first time by considering the transition of the railcar state. On this basis, an improved A* algorithm based on the railcar flow route was proposed to generate feasible path sets and a dynamic railcar flow distribution model was built to simulate the railcar flow distribution process in an emergency. In our numerical studies, these output results of our proposed model can be used to control traffic congestion.

A network model for solving the yard truck routing and scheduling problem

2016 ◽  
Vol 27 (2) ◽  
pp. 353-370
Author(s):  
Feng-Ming Tsai ◽  
Chung-Cheng Lu ◽  
Yu-Ming Chang
Keyword(s):  
Network Model ◽  
Waiting Time ◽  
Queuing Theory ◽  
Operating Cost ◽  
Container Terminals ◽  
Scheduling Problem ◽  
Content Type ◽  
Routing And Scheduling ◽  
Space Network ◽  
Time Space

Purpose – The purpose of this paper is to improve the efficiency of loading and discharging operations in container terminals. Accounting for an increase in the size of ships, the yard truck (YT) routing and scheduling problem has become an important issue to terminal operators. Design/methodology/approach – A (binary) integer programming model is developed using the time-space network technique to optimally move YTs between quay cranes (QC) and yard cranes (YC) in the time and space dimensions. The objective of the model is to minimize the total operating cost, and the model employs the M/M/S model in the queuing theory to determine the waiting time of YTs. The developed model can obtain the optimal number of YTs and their scheduling and routing plans simultaneously, as shown by the computational results. Findings – The results also show that the model can be applied to practical operations. In this research, an experimental design of the QC and YC operation networks was considered with the import and export containers carried by YTs. The model can be used to tackle a real world problem in an international port, and the analysis results could be useful references for port operators in actual practice. Research limitations/implications – The purpose of this research only focusses on YTs routing and scheduling problem, however, the container terminal operation problems are interrelated with berth allocation and yard stacking plan. The managerial application of this study is to analyze the trade-off between truck numbers and truck waiting time can be used for terminal operators to adjust the truck assignment. This research can assist an operator to determine the optimal fleet size and schedule in advance to avoid wasted costs and congestion in the quayside and yard block. Originality/value – This research solves the YT scheduling and routing problem for container discharging and loading processes with a time-space network model, which has not been previously reported, through an empirical research.

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