A near-optimal algorithm for constraint test ordering in automated stowage planning
The container stowage planning problem is known to be NP-hard and heuristic algorithms have been proposed. Conventionally, the efficiency of the stowage planning algorithms are improved by pruning or reducing the search space. We observe that constraint evaluation is the core of most algorithms. I...
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sg-ntu-dr.10356-1061212019-12-06T22:04:58Z A near-optimal algorithm for constraint test ordering in automated stowage planning Lee, Zhuo Qi Fan, Rui Hsu, Wen-Jing School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Automation Logistics The container stowage planning problem is known to be NP-hard and heuristic algorithms have been proposed. Conventionally, the efficiency of the stowage planning algorithms are improved by pruning or reducing the search space. We observe that constraint evaluation is the core of most algorithms. In addition, the order at which the constraints are evaluated can have significant impact on the efficiency of the constraint evaluation engine. We propose random sample model (RSM) and sequential sample model (SSM) for analysis of the problem. We present and evaluate seven strategies in optimizing the constraint evaluation engine. We show how to achieve the optimal constraint ordering with respect to RSM and SSM, respectively. However, the optimal ordering for SSM requires perfect information about the states of the constraint tests, which is impractical. We present an alternative strategy and show empirically that its efficiency is close to the optimal. Experiments show that, compared to a naïve ordering, an average of 2.74 times speed up in the evaluation engine can be achieved. Accepted version 2019-03-22T07:24:13Z 2019-12-06T22:04:58Z 2019-03-22T07:24:13Z 2019-12-06T22:04:58Z 2018 Journal Article Lee, Z. Q., Fan, R., & Hsu, W.- J. (2018). A near-optimal algorithm for constraint test ordering in automated stowage planning. IEEE Transactions on Automation Science and Engineering, 15(3), 1298-1308. doi:10.1109/TASE.2017.2779470 1545-5955 https://hdl.handle.net/10356/106121 http://hdl.handle.net/10220/47888 http://dx.doi.org/10.1109/TASE.2017.2779470 en IEEE Transactions on Automation Science and Engineering © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TASE.2017.2779470 12 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Automation Logistics Lee, Zhuo Qi Fan, Rui Hsu, Wen-Jing A near-optimal algorithm for constraint test ordering in automated stowage planning |
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The container stowage planning problem is known to be NP-hard and heuristic
algorithms have been proposed. Conventionally, the efficiency of the stowage planning algorithms are improved by pruning or reducing the search space. We observe that constraint evaluation is the core of most algorithms. In addition, the order at which the constraints are evaluated can have significant impact on the efficiency of the constraint evaluation engine. We propose random sample model (RSM) and sequential sample model (SSM) for analysis of the problem. We present and evaluate seven strategies in optimizing the constraint evaluation engine. We show how to achieve the optimal constraint ordering with respect to RSM and SSM, respectively. However, the optimal ordering for SSM requires perfect information about the states of the constraint tests, which is impractical. We present an alternative strategy and show empirically that its efficiency is close to the optimal. Experiments show that, compared to a naïve ordering, an average of 2.74 times speed up in the evaluation engine can be achieved. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Lee, Zhuo Qi Fan, Rui Hsu, Wen-Jing |
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Article |
author |
Lee, Zhuo Qi Fan, Rui Hsu, Wen-Jing |
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Lee, Zhuo Qi |
title |
A near-optimal algorithm for constraint test ordering in automated stowage planning |
title_short |
A near-optimal algorithm for constraint test ordering in automated stowage planning |
title_full |
A near-optimal algorithm for constraint test ordering in automated stowage planning |
title_fullStr |
A near-optimal algorithm for constraint test ordering in automated stowage planning |
title_full_unstemmed |
A near-optimal algorithm for constraint test ordering in automated stowage planning |
title_sort |
near-optimal algorithm for constraint test ordering in automated stowage planning |
publishDate |
2019 |
url |
https://hdl.handle.net/10356/106121 http://hdl.handle.net/10220/47888 http://dx.doi.org/10.1109/TASE.2017.2779470 |
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