**When:** 3:30 pm, Wed, 27th Oct 2010

**Room:** V206, Mathematics Building

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**Speaker:** Angelos Tsoukalas , School of Mathematical and Geospatial Sciences, RMIT University

**Title:** * Using Cutting Planes in the Feasibility Pump*
**Abstract:** We discuss the feasibility pump heuristic and we interpret it as a multi-start, global optimization algorithm that utilizes a fast local minimizer. The function that is minimized has many local minima, some of which correspond to feasible integral solutions. This interpretation suggests alternative ways of incorporating restarts one of which is the use of cutting planes to eliminate local optima that do not correspond to feasible integral solutions. Numerical experiments show encouraging results on standard test libraries.

**When:** 11:30 am, Fri, 10th Sep 2010

**Room:** V205, Mathematics Building

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**Speaker:** Dr Victoria Martín-Márquez, Department of Mathematical Analysis, Universidad de Sevilla

**Title:** *Recent advances in nonexpansive and monotone operator theory in Hadamard manifolds*
**Abstract:** *Riemannian manifolds constitute a broad and fruitful framework for the development of different fields in mathematic, such as convex analysis, dynamical systems, optimization or mathematical programming, among other scientific areas, where some of its approaches and methods have successfully been extended from Euclidean spaces. The nonpositive sectional curvature is an important property enjoyed by a large class of differential manifolds, so Hadamard manifolds, which are complete simply connected Riemannian manifolds of nonpositive sectional curvature, have worked out a suitable setting for diverse disciplines.*On the other hand, the study of the class of nonexpansive mappings has become an active research area in nonlinear analysis. This is due to the connection with the geometry of Banach spaces along with the relevance of these mappings in the theory of monotone and accretive operators.

*We study the problems that arise in the interface between the fixed point theory for nonexpansive type mappings and the theory of monotone operators in the setting of Hadamard manifolds. Different classes of monotone and accretive set-valued vector fields and the relationship between them will be presented, followed by the study of the existence and approximation of singularities for such vector fields. Then we analyze the problem of finding fixed points of nonexpansive type mappings and the connection with monotonicity. As a consequence, variational inequality and minimization problems in this setting will be discussed.*

**When:** 11:30 am, Fri, 27th Aug 2010

(11:00 am Adelaide time.)

**Room:** V205, Mathematics Building

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**Speaker:** Andreas Hamel, Department of Operations Research and Financial Engineering, Princeton University

**Title:** *The Fundamental Duality Formula in Set-Valued Optimization*

**Abstract:** *The fundamental duality formula (see Zalinescu ”Convex Analysis in General Vector Spaces”, Theorem 2.7.1) is extended to functions mapping into the power set of a topological linear space with a convex cone which is not necessarily pointed. Pairs of linear functionals are used as dual variables instead of linear operators. The talk will consist of three parts. First, motivations and explanations are given for the infimum approach to set-valued optimization. It deviates from other approaches, and it seems to be the only way to obtain a theory which completely resembles the scalar case. In the second part, the main results are presented, namely the fundamental duality formula and several conclusions. The third part deals with duality formulas for set-valued risk measures, a cutting edge development in mathematical finance. It turns out that the proposed duality theory for set-valued functions provides a satisfying framework not only for set-valued risk measures, but also for no-arbitrage and superhedging theorems in conical market models.*

**When:** 2:30 pm, Wed, 18th Aug 2010

**Room:** V205, Mathematics Building

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**Speaker:** Stephen Simons, Department of Mathematics, University of California, Santa Barbara

**Title:** *The Hahn-Banach-Lagrange Theorem*

**Abstract:** *We discuss the Hahn-Banach-Lagrange theorem, a generalized form of the Hahn--Banach theorem. As applications, we derive various results on the existence of linear functionals in functional analysis, on the existence of Lagrange multipliers for convex optimization problems, with an explicit sharp lower bound on the norm of the solutions (multipliers), on finite families of convex functions (leading rapidly to a minimax theorem), on the existence of subgradients of convex functions, and on the Fenchel conjugate of a convex function. We give a complete proof of Rockafellar's version of the Fenchel duality theorem, and an explicit sharp lower bound for the norm of the solutions of the Fenchel duality theorem in terms of elementary geometric concepts.*

**When:** 4:00 pm, Thu, 24th Jun 2010

**Room:** V206, Mathematics Building

**Access Grid Venue:** Andrew.Danson@newcastle.edu.au

**Speaker:** Conjoint Prof Steve Wright, Computer Sciences Department and Wisconsin Institute for Discovery, University of Wisconsin-Madison

**Title:** *More Tools and Applications of Sparse Optimization*

**Abstract:** *Machine learning problems are a particularly rich source of applications for sparse optimization, giving rise to a number of formulations that require specialized solvers and structured, approximate solutions. As case studies, we discuss two such applications - sparse SVM classification and sparse logistic regression - and present algorithms that are assembled from different components, including stochastic gradient methods, random approximate matrix factorizations, block coordinate descent, and projected Newton methods. We also describe a third (distantly related) application to selection of captive breeding populations for endangered species using binary quadratic programming, a project started during a visit to Newcastle in June 2009.*

**When:** 2:00 pm, Wed, 9th Jun 2010

**Room:** V206, Mathematics Building

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**Speaker:** Dr C. Yalcin Kaya, University of South Australia

**Title:** *Numerical Methods For Convex Multi-objective Control Problems*

**Abstract:** *We consider multi-objective convex optimal control problems. First we state a relationship between the (weakly or properly) efficient set of the multi-objective problem and the solution of the problem scalarized via a convex combination of objectives through a vector of parameters (or weights). Then we establish that (i) the solution of the scalarized (parametric) problem for any given parameter vector is unique and (weakly or properly) efficient and (ii) for each solution in the (weakly or properly) efficient set, there exists at least one corresponding parameter vector for the scalarized problem yielding the same solution. Therefore the set of all parametric solutions (obtained by solving the scalarized problem) is equal to the efficient set. Next we consider an additional objective over the efficient set. Based on the main result, the new objective can instead be considered over the (parametric) solution set of the scalarized problem. For the purpose of constructing numerical methods, we point to existing solution differentiability results for parametric optimal control problems. We propose numerical methods and give an example application to illustrate our approach. This is joint work with Henri Bonnel (University of New Caledonia).*