Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals

One of the common problems a yard crane dispatcher in the container terminal faces every day is to complete the given jobs on time as it is predicted. As the quay cranes’ operations depend greatly on the arriving and departing of vehicles, the vehicle must make sure not to make any delays in their s...

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Main Author: Li, Iemin
Other Authors: Huang Shell Ying
Format: Final Year Project
Language:English
Published: 2014
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Online Access:http://hdl.handle.net/10356/58943
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-589432023-03-03T20:58:23Z Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals Li, Iemin Huang Shell Ying School of Computer Engineering DRNTU::Engineering One of the common problems a yard crane dispatcher in the container terminal faces every day is to complete the given jobs on time as it is predicted. As the quay cranes’ operations depend greatly on the arriving and departing of vehicles, the vehicle must make sure not to make any delays in their schedule. It is easy for the dispatcher to predict the vehicle arrival time based on the given job schedule. However some time it is difficult for the driver of a vehicle to arrive to the specific loading and unloading point at yard block on the predicted time as movement of vehicle is a dynamic process and incident may occur in the midst of travelling from point to point. Thus it makes it hard to predict the actual vehicle arrival time. Two algorithms, MMT-RBA and MMT-localSeach, are presented to find the Yard Crane job sequence for serving a fleet of vehicle with actual arrival time. MMT-RBA is provable to find the optimal job sequence by using recursive backtracking with A* algorithm to re-compute remaining jobs that fall after the deviated job , whereas MMT-localSearch selects a few jobs around the deviated job and do a local search to find best sequence to minimize the maximum tardiness. Simulation of the deviation from predicted vehicle arrival time is computed by sampling a random value from a probability distribution with the predicted arrival time as the mean. The result of the experiment shows that recomputation by RBA performs better than no-computation and local search. However, based on statistical means, it shows that recomputation by RBA, the vehicle waiting time are statistically lower even though there is no statistical difference in the other performance indicators like tardiness, makespan and YC travelling distance. Bachelor of Engineering (Computer Science) 2014-04-16T04:33:27Z 2014-04-16T04:33:27Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/58943 en Nanyang Technological University 51 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Li, Iemin
Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
description One of the common problems a yard crane dispatcher in the container terminal faces every day is to complete the given jobs on time as it is predicted. As the quay cranes’ operations depend greatly on the arriving and departing of vehicles, the vehicle must make sure not to make any delays in their schedule. It is easy for the dispatcher to predict the vehicle arrival time based on the given job schedule. However some time it is difficult for the driver of a vehicle to arrive to the specific loading and unloading point at yard block on the predicted time as movement of vehicle is a dynamic process and incident may occur in the midst of travelling from point to point. Thus it makes it hard to predict the actual vehicle arrival time. Two algorithms, MMT-RBA and MMT-localSeach, are presented to find the Yard Crane job sequence for serving a fleet of vehicle with actual arrival time. MMT-RBA is provable to find the optimal job sequence by using recursive backtracking with A* algorithm to re-compute remaining jobs that fall after the deviated job , whereas MMT-localSearch selects a few jobs around the deviated job and do a local search to find best sequence to minimize the maximum tardiness. Simulation of the deviation from predicted vehicle arrival time is computed by sampling a random value from a probability distribution with the predicted arrival time as the mean. The result of the experiment shows that recomputation by RBA performs better than no-computation and local search. However, based on statistical means, it shows that recomputation by RBA, the vehicle waiting time are statistically lower even though there is no statistical difference in the other performance indicators like tardiness, makespan and YC travelling distance.
author2 Huang Shell Ying
author_facet Huang Shell Ying
Li, Iemin
format Final Year Project
author Li, Iemin
author_sort Li, Iemin
title Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
title_short Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
title_full Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
title_fullStr Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
title_full_unstemmed Handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
title_sort handling arrival time uncertainties in yard crane dispatching to minimize job tardiness in container terminals
publishDate 2014
url http://hdl.handle.net/10356/58943
_version_ 1759854641698308096