15th EUROPT Workshop on Advances in Continuous Optimization

Montréal, Canada, 12 — 14 juillet 2017

15th EUROPT Workshop on Advances in Continuous Optimization

Montréal, Canada, 12 — 14 juillet 2017

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In Memory of Roger Fletcher: Large-Scale Optimization

13 juil. 2017 09h45 – 11h00

Salle: Amphithéâtre Banque Nationale

Présidée par Sven Leyffer

3 présentations

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    09h45 - 10h10

    Novel update techniques for the revised simplex method

    • Julian Hall, prés., University of Edinburgh
    • Qi Huangfu, FICO

    The development of techniques for creating and updating the invertible representation of the simplex basis matrix were a feature of my PhD studies under Roger in 1987-90. So it is appropriate that this talk presents recent recent work in this area. Specifically, it will describe two variants of the product form update and the multiple Forrest-Tomlin update which are valuable in the context of a recently released high performance revised simplex solver.

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    10h10 - 10h35

    On the behavior of a Class of Symmetric Conjugate Gradient Methods for Large-Scale Optimization

    • Mehiddin Al-Baali, prés., Sultan Qaboos University

    A recent class of symmetric conjugate gradient methods for large-scale unconstrained optimization will be considered. The class, with any line search, suggests strategies for enforcing the sufficient descent and other useful properties. Numerical results on a set of standard test problems will be described. They show that the proposed symmetrical-strategy improves the performance of several conjugate gradient methods substantially (in particular, those of the well-known Fletcher-Reeves, Polak-Ribi\'{e}re and Hestenes-Stiefel methods).

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    10h35 - 11h00

    Nonlinear optimization problems on the sphere

    • Robert Womersley, prés., University of New South Wales

    The problem of placing N points uniformly on the unit sphere has many different solutions depending on the particular objective: Riesz s-energy, separation/packing, covering, numerical integration (including spherical t-designs) and approximation. Different parametrizations of the variables, either as points in Euclidean space, spherical coordinates or positive semi-definite matrices of inner products with a rank condition, each have their own advantages and disadvantages. The aim is to have many (millions) points, and a global minimizer, when these highly nonlinear problems are characterized by many different local minimizers. Here there are applications for a wide range of efficient scalable nonlinear optimzation algorithms - areas that greatly benefited from Roger Fletcher's pioneering work.