rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: New conjugate gradient and its hybrid method for unconstrained optimization problems
  name:
    name part: Nurul 'Aini Harun
    role:
      role term: creator
    role:
      role term: author
  name:
    name part: Universiti Sultan Zainal Abidin
    name part: Faculty of Informatics and computing
  type of resource: text
  genre: Dissertations, Academic
  origin info:
    place:
      place term: my
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xvi, 252 leaves : illustrations (some colour) ; 30cm.
  abstract: There are several methods for solving unconstrained optimization functions. Of these methods, the ones most commonly u ed are the conjugate gradient (CG) and quasi¬Newton (QN) method. The CG approach is suitable for large scale problems because of its low memory requirement. However, most developments in the CG method involve complex equation for its search direction, making it difficult to implement. Some of them are also not globally convergent. The QN method is efficient for solving problems of small and medium cale though it becomes increasingly slow when applied to large-scale problems. This is due to the n x n matrix in its search direction formula that leads to high memory requirement. In this study, a globally convergent CG coefficient is presented. The new algorithm is based on cia sical CG which is simple and also efficient in solving unconstrained optimization problems. Next, to improve the efficiency of the QN method, a hybrid search direction of QN and CG method is proposed. The CG method is chosen for its computational capability in solving large scale problems and good convergence properties. The CG coefficient proposed in this thesis is used in the hybrid search direction. The new algorithms are shown to possess sufficient descent and global convergence propertie when used with strong Wolfe line search. For the numerical tests, twenty-five standard functions are used with varying dimension levels and starting points. The test measures the performance of the solvers in terms of iteration number and CPU time. All of the computation process is performed by Matlab r2012 programme. The performance of the new CG method is compared with some of the current CG methods while the new hybrid QN method is compared with the original QN and two existing hybrid QN methods. An application in data fitting is also included to prove the applicability of the new approaches in real life problem. Based on the numerical results, the proposed CG has the highest number of te…
  table of contents: 1. Research overview -- 2. Basic concepts of unconstrained optimization -- 3. Methodology -- 4. Modification of conjugate gradient method -- 5. Hybrid quasi-newton method -- 6. Application in regression analysis -- 7. Conclusion
  note: Nurul 'Aini Binti Harun
  note: Thesis (Degree of Doctor of Philosophy) - Universiti Sultan Zainal Abidin, 2017
  note: Includes bibliographical references (leaves 157-167)
  subject:
    name:
      name part: Universiti Sultan Zainal Abidin
    topic: Faculty of Informatics and Computing
    genre: Dissertations
  subject:
    topic: Conjugate gradient methods
  subject:
    topic: Conjugate gradient methods-Data processing
  classification: QA218 .N878 2017
  record info:
    record content source: UniSZA
    record creation date: 180227
    record change date: 20200723093000.0
    record identifier: 0000094039