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

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

Content Provider	Semantic Scholar
Author	Thomas, Jaya Chaudhari, N. S.
Copyright Year	2014
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.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.vincentgaspersz.com/wp-content/uploads/2018/07/J%20Thomas%20NS%20Chaudhari%20-%20A%20new%20metaheuristic%20genetic-based%20placement%20algorithm%20for%202D%20strip%20packing.pdf
Language	English
Access Restriction	Open
Subject Keyword	Appendix Benchmark (computing) Combinatorial optimization Computation Convergence (action) Crossover (genetic algorithm) Fitness function Gallium Genetic algorithm HL7PublishingSubSection Heuristic Large License Mathematical optimization Metaheuristic NP-hardness Population Self-propelled particles Set packing Silo (dataset) Software release life cycle Solutions Tab stop Time complexity Xfig width
Content Type	Text
Resource Type	Article

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