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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書誌詳細
出版年:Journal of Physics: Conference Series
第一著者: 2-s2.0-85079685148
フォーマット: Conference paper
言語:English
出版事項: Institute of Physics Publishing 2020
オンライン・アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079685148&doi=10.1088%2f1742-6596%2f1447%2f1%2f012041&partnerID=40&md5=e59b29916d95c11f1a4b116258dd280e
その他の書誌記述
要約: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. © Published under licence by IOP Publishing Ltd.
ISSN:17426588
DOI:10.1088/1742-6596/1447/1/012041