Optimisation model and exact algorithm for autonomous straddle carrier scheduling at automated container terminals

Cai, B; Huang, S; Liu, D; Yuan, S; Dissanayake, G; Lau, H; Pagac, D

Optimisation model and exact algorithm for autonomous straddle carrier scheduling at automated container terminals

Cai, B

Huang, S

Liu, D

Yuan, S Dissanayake, G

Lau, H Pagac, D

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2011, pp. 3686 - 3693
Issue Date:: 2011-12-29

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Field	Value	Language
dc.contributor.author	Cai, B https://orcid.org/0000-0002-0348-0690	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.contributor.author	Yuan, S	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Lau, H	en_US
dc.contributor.author	Pagac, D	en_US
dc.date.issued	2011-12-29	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2011, pp. 3686 - 3693	en_US
dc.identifier.isbn	9781612844541	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32363
dc.description.abstract	In this paper, an optimisation model based on Pickup and Delivery Problem with Time Windows (PDPTW), and an exact algorithm based on Branch-and-Bound with Column Generation (BBCG), are presented for Autonomous Straddle Carriers Scheduling (ASCS) problem at automated container terminals. The ASCS problem is firstly modeled into a PDPTW, which is formulated as a Binary Integer Programming (BIP) and then solved by Column Generation (CG) in the Branch-and-Bound (BB) framework. The BBCG algorithm is also compared to another two exact algorithms [i.e., Binary integer Programming with Dynamic Programming (BPDP) and Exhaustive Search with Permutation and Combination (ESPC)] for the ASCS problem solving. Based on the map of an actual automated container terminal, simulation results and discussions are presented to demonstrate the effectiveness and efficiency of the presented model and algorithm for autonomous vehicle scheduling. © 2011 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/LP0882745
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2011.6048404	en_US
dc.title	Optimisation model and exact algorithm for autonomous straddle carrier scheduling at automated container terminals	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	San Francisco, CA
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In this paper, an optimisation model based on Pickup and Delivery Problem with Time Windows (PDPTW), and an exact algorithm based on Branch-and-Bound with Column Generation (BBCG), are presented for Autonomous Straddle Carriers Scheduling (ASCS) problem at automated container terminals. The ASCS problem is firstly modeled into a PDPTW, which is formulated as a Binary Integer Programming (BIP) and then solved by Column Generation (CG) in the Branch-and-Bound (BB) framework. The BBCG algorithm is also compared to another two exact algorithms [i.e., Binary integer Programming with Dynamic Programming (BPDP) and Exhaustive Search with Permutation and Combination (ESPC)] for the ASCS problem solving. Based on the map of an actual automated container terminal, simulation results and discussions are presented to demonstrate the effectiveness and efficiency of the presented model and algorithm for autonomous vehicle scheduling. © 2011 IEEE.

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http://hdl.handle.net/10453/32363