A new metaheuristic genetic-based placement algorithm for 2D strip packing

Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard c...

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Published inJournal of industrial engineering international Vol. 10; no. 1; pp. 1 - 16
Main Authors Thomas, Jaya, Chaudhari, Narendra S
Format Journal Article
LanguageEnglish
Published Heidelberg Springer 01.04.2014
Springer Berlin Heidelberg
Islamic Azad University, South Tehran Branch
Subjects
Combinatorial optimization
Crossover
Engineering
Engineering Economics
Facility Management
Fitness
Genetic algorithm
Industrial and Production Engineering
Logistics
Marketing
Mathematical and Computational Engineering
Operation research
Organization
Original Research
Placement approach
Quality Control
Reliability
Safety and Risk
Strip packing
Genetic algorithm
Combinatorial optimization
Crossover
Operation research
Placement approach
Strip packing
Fitness
Online AccessGet full text
ISSN2251-712X
1735-5702
2251-712X
DOI10.1007/s40092-014-0047-9

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Abstract Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. In this paper, we give a hybrid approach which combined genetic encoding and evolution scheme with the proposed placement approach. Such a combination resulted in better population evolution and faster solution convergence to optimal. The approach is subjected to a comprehensive test using benchmark instances. The computation results validate the solution and the effectiveness of the approach.
AbstractList Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. In this paper, we give a hybrid approach which combined genetic encoding and evolution scheme with the proposed placement approach. Such a combination resulted in better population evolution and faster solution convergence to optimal. The approach is subjected to a comprehensive test using benchmark instances. The computation results validate the solution and the effectiveness of the approach.
ArticleNumber 47
Author Chaudhari, Narendra S
Thomas, Jaya
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Issue 1
Keywords Genetic algorithm
Combinatorial optimization
Crossover
Operation research
Placement approach
Strip packing
Fitness
Language English
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Snippet Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the...
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SubjectTerms Combinatorial optimization
Crossover
Engineering
Engineering Economics
Facility Management
Fitness
Genetic algorithm
Industrial and Production Engineering
Logistics
Marketing
Mathematical and Computational Engineering
Operation research
Organization
Original Research
Placement approach
Quality Control
Reliability
Safety and Risk
Strip packing
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Title A new metaheuristic genetic-based placement algorithm for 2D strip packing
URI https://www.econstor.eu/handle/10419/157391
https://link.springer.com/article/10.1007/s40092-014-0047-9
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