Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/157391
Authors: 
Thomas, Jaya
Chaudhari, Narendra S.
Year of Publication: 
2014
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 10 [Year:] 2014 [Pages:] 1-16
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.
Subjects: 
Combinatorial optimization
Crossover
Fitness
Genetic algorithm
Operation research
Placement approach
Strip packing
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/2.0/
Document Type: 
Article

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