Algorithms for Constrained Best-fit Alignment

Authors

  • Laure Devendeville MIS EA 4290, Université de Picardie Jules Verne, 33 rue Saint-Leu, 80039 Amiens cedex 1
  • Serge Dumont LAMFA CNRS UMR 7352, Université de Picardie Jules Verne, 33 rue Saint-Leu, 80039 Amiens cedex 1
  • Olivier Goubet LAMFA CNRS UMR 7352, Université de Picardie Jules Verne, 33 rue Saint-Leu, 80039 Amiens cedex 1
  • Sylvain Lefebvre

DOI:

https://doi.org/10.26713/jims.v5i2.180

Keywords:

Non convex constrained optimization problems, Steepest descent with projection algorithm and stochastic local search algorithm

Abstract

Manufacturing complex structures as planes requires the assembly of several pieces. The first step in the process is to align the pieces. This article is concerned with some mathematical and computational aspects of new  algorithms devoted to the alignment of the pieces. We describe the properties of suitable algorithms to handle a non standard constrained optimization problem that occurs in the assembly process of a manufactured product. Then we present two kinds of algorithms: the first based on a fractional step algorithm and the second on a local search algorithm. We assess them on real cases and compare their results with an evolutionary algorithm for difficult non-linear or non-convex optimization problems in continuous domain.

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CITATION

How to Cite

Devendeville, L., Dumont, S., Goubet, O., & Lefebvre, S. (2013). Algorithms for Constrained Best-fit Alignment. Journal of Informatics and Mathematical Sciences, 5(2), 77–100. https://doi.org/10.26713/jims.v5i2.180

Issue

Vol. 5 No. 2 (2013)

Section

Research Articles

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