An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints View Full Text


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Article Info

DATE

2018-03

AUTHORS

G. Cocchi, G. Liuzzi, A. Papini, M. Sciandrone

ABSTRACT

This paper is concerned with the definition of new derivative-free methods for box constrained multiobjective optimization. The method that we propose is a non-trivial extension of the well-known implicit filtering algorithm to the multiobjective case. Global convergence results are stated under smooth assumptions on the objective functions. We also show how the proposed method can be used as a tool to enhance the performance of the Direct MultiSearch (DMS) algorithm. Numerical results on a set of test problems show the efficiency of the implicit filtering algorithm when used to find a single Pareto solution of the problem. Furthermore, we also show through numerical experience that the proposed algorithm improves the performance of DMS alone when used to reconstruct the entire Pareto front. More... »

PAGES

267-296

References to SciGraph publications

  • 2002-01. Benchmarking optimization software with performance profiles in MATHEMATICAL PROGRAMMING
  • 1998. Nonlinear Multiobjective Optimization in NONE
  • 2008. Multiobjective Genetic Algorithms in NETWORK MODELS AND OPTIMIZATION
  • 1995. Implicit Filtering and Optimal Design Problems in OPTIMAL DESIGN AND CONTROL
  • 2009-04. Decomposition Algorithm Model for Singly Linearly-Constrained Problems Subject to Lower and Upper Bounds in JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
  • 2000-08. Steepest descent methods for multicriteria optimization in MATHEMATICAL METHODS OF OPERATIONS RESEARCH
  • 2004-06. Solution of a Well-Field Design Problem with Implicit Filtering in OPTIMIZATION AND ENGINEERING
  • 2007-11. A convergent decomposition algorithm for support vector machines in COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
  • 2007. Combining of Differential Evolution and Implicit Filtering Algorithm Applied to Electromagnetic Design Optimization in SOFT COMPUTING IN INDUSTRIAL APPLICATIONS
  • 2001-06. Algorithms for Noisy Problems in Gas Transmission Pipeline Optimization in OPTIMIZATION AND ENGINEERING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10589-017-9953-2

    DOI

    http://dx.doi.org/10.1007/s10589-017-9953-2

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