Implementation of Discrete Capability into the enhanced Multipoint Approximation Method for solving mixed integer-continuous optimization problems

Dianzi Liu, Vassili Toropov

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
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Abstract

Multipoint approximation method (MAM) focuses on the development of metamodels for the objective and constraint functions in solving a mid-range optimization problem within a trust region. To develop an optimization technique applicable to mixed integer-continuous design optimization problems in which the objective and constraint functions are computationally expensive and could be impossible to evaluate at some combinations of design variables, a simple and efficient algorithm, coordinate search, is implemented in the MAM. This discrete optimization capability is examined by the well established benchmark problem and its effectiveness is also evaluated as the discreteness interval for discrete design variables is increased from 0.2 to 1. Furthermore, an application to the optimization of a lattice composite fuselage structure where one of design variables (number of helical ribs) is integer is also presented to demonstrate the efficiency of this capability.
Original languageEnglish
Pages (from-to)22-35
Number of pages14
JournalInternational Journal for Computational Methods in Engineering Science & Mechanics
Volume17
Issue number1
Early online date28 Jan 2016
DOIs
Publication statusPublished - 21 Mar 2016

Keywords

  • Multipoint approximation method
  • Integer-continuous optimization
  • Metamodel
  • Coordinate search

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