Smart packing simulator for 3D packing problem using genetic algorithm

Every year, at least 100 million tons of solid waste globally comes from packaging waste, in which partly created by inefficient packaging. Multiple box arrangement or bin packing solution directly addresses this problem which also affects storing space in production, manufacturing and logistics sec...

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Main Authors: Khairuddin, Uswah, M. Razi, N. A. Z., Z. Abidin, M. S., Yusof, R.
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Online Access:http://eprints.utm.my/id/eprint/93438/1/UswahKhairuddin2020_SmartPackingSimulatorfor3D.pdf
http://eprints.utm.my/id/eprint/93438/
http://dx.doi.org/10.1088/1742-6596/1447/1/012041
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spelling my.utm.934382021-11-30T08:33:26Z http://eprints.utm.my/id/eprint/93438/ Smart packing simulator for 3D packing problem using genetic algorithm Khairuddin, Uswah M. Razi, N. A. Z. Z. Abidin, M. S. Yusof, R. Q Science (General) T58.5-58.64 Information technology Every year, at least 100 million tons of solid waste globally comes from packaging waste, in which partly created by inefficient packaging. Multiple box arrangement or bin packing solution directly addresses this problem which also affects storing space in production, manufacturing and logistics sector. Smart packing algorithm is designed for solving three-dimensional bin/container packing problem (3DBPP) which has numerous practical applications in various fields including container ship loading, pallet loading, plane cargo, warehouse management and parcel packing. This project investigates the implementation of genetic algorithm (GA) for a smart packing simulator in solving the 3DBPP applications. The smart packing system has an adaptable chromosome length GA for more robust implementation, where chromosome length will be changing with number of boxes. It can optimize multiple box arrangements and the boxes movements and positions are simulated through each GA generations, for realistic adaptation. The system is able to make optimum arrangement for the boxes so they can fit into a smallest container possible. The time taken for GA to converge varies with number of boxes. 2020-01-31 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/93438/1/UswahKhairuddin2020_SmartPackingSimulatorfor3D.pdf Khairuddin, Uswah and M. Razi, N. A. Z. and Z. Abidin, M. S. and Yusof, R. (2020) Smart packing simulator for 3D packing problem using genetic algorithm. In: 4th International Conference on Advanced Technology and Applied Sciences, ICaTAS 2019, 10 September 2019 - 12 September 2019, Cairo, Egypt. http://dx.doi.org/10.1088/1742-6596/1447/1/012041
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic Q Science (General)
T58.5-58.64 Information technology
spellingShingle Q Science (General)
T58.5-58.64 Information technology
Khairuddin, Uswah
M. Razi, N. A. Z.
Z. Abidin, M. S.
Yusof, R.
Smart packing simulator for 3D packing problem using genetic algorithm
description Every year, at least 100 million tons of solid waste globally comes from packaging waste, in which partly created by inefficient packaging. Multiple box arrangement or bin packing solution directly addresses this problem which also affects storing space in production, manufacturing and logistics sector. Smart packing algorithm is designed for solving three-dimensional bin/container packing problem (3DBPP) which has numerous practical applications in various fields including container ship loading, pallet loading, plane cargo, warehouse management and parcel packing. This project investigates the implementation of genetic algorithm (GA) for a smart packing simulator in solving the 3DBPP applications. The smart packing system has an adaptable chromosome length GA for more robust implementation, where chromosome length will be changing with number of boxes. It can optimize multiple box arrangements and the boxes movements and positions are simulated through each GA generations, for realistic adaptation. The system is able to make optimum arrangement for the boxes so they can fit into a smallest container possible. The time taken for GA to converge varies with number of boxes.
format Conference or Workshop Item
author Khairuddin, Uswah
M. Razi, N. A. Z.
Z. Abidin, M. S.
Yusof, R.
author_facet Khairuddin, Uswah
M. Razi, N. A. Z.
Z. Abidin, M. S.
Yusof, R.
author_sort Khairuddin, Uswah
title Smart packing simulator for 3D packing problem using genetic algorithm
title_short Smart packing simulator for 3D packing problem using genetic algorithm
title_full Smart packing simulator for 3D packing problem using genetic algorithm
title_fullStr Smart packing simulator for 3D packing problem using genetic algorithm
title_full_unstemmed Smart packing simulator for 3D packing problem using genetic algorithm
title_sort smart packing simulator for 3d packing problem using genetic algorithm
publishDate 2020
url http://eprints.utm.my/id/eprint/93438/1/UswahKhairuddin2020_SmartPackingSimulatorfor3D.pdf
http://eprints.utm.my/id/eprint/93438/
http://dx.doi.org/10.1088/1742-6596/1447/1/012041
_version_ 1718926068062093312
score 13.15806