NDLI: Evolutionary search techniques application in automated layout-planning optimization problem

Content Provider	IEEE Xplore Digital Library
Author	Bounsaythip, C. Maouche, S. Neus, M.
Copyright Year	1995
Description	Author affiliation: Centre d'Autom. de Lille, Univ. des Sci. et Tech. de Lille Flandres Artois, Villeneuve d'Ascq, France (Bounsaythip, C.; Maouche, S.; Neus, M.)
Abstract	The purpose of this paper fits in optimization of apparel shapes layout. The aim is to mark all the shapes to be cut onto the sheet by minimizing unoccupied spaces. As the problem involves many sub-optimal solutions or many local optima, genetic-like algorithm is used to handle the layout process. The application of genetic algorithm (GA) needs parameter encoding. At first, an individual is encoded by combs coordinates of shape description. Strings are of variable length and genetic operators are created to this domain specific encoding. As genetic algorithm used alone is not very efficient, we made attempt to hybridize GA with simulated annealing (SA). Results provided are compared with GA alone and with our previous results by tree search.
Starting Page	4497
Ending Page	4502
File Size	554031
Page Count	6
File Format	PDF
ISBN	0780325591
DOI	10.1109/ICSMC.1995.538503
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-10-22
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Genetic algorithms Costs State estimation Encoding Simulated annealing Postal services Humans Art NP-hard problem
Content Type	Text
Resource Type	Article

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