Academic Publications and Presentations

2006

• Multi-Stage Investment Decision under Contingent Demand for Networking Planning (Presnetation)Miguel F. Anjos, Michael Desroches, Anwar Haque, Oleg Grodzevich, Hua Wei, Henry WolkowiczPresented at IEEE GLOBECOM 2006 Conference in San Francisco, CA
• Discussions on Normalization and Other Topics in Multi-Objective OptimizationOleg Grodzevich et al.To appear in Proceedings to the Fields-MITACS Industrial Problem Solving Workshop, Toronto In this report we consider a convex multi-objective optimization problem with linear and quadratic objectives typically appearing in financial applications. The problem is posed by the Algorithmics Inc. We focus on techniques for the normalization of objective functions in order to make optimal solutions consistent with the decision maker preferences. We provide an algorithm that combines both weighted sum and hierarchical approaches to solve the aforementioned problem.
• Multi-Stage Investment Decision under Contingent Demand for Networking PlanningMiguel F. Anjos, Michael Desroches, Anwar Haque, Oleg Grodzevich, Hua Wei, Henry WolkowiczTo appear in Proceedings of the 2006 IEEE GLOBECOM Conference in San Francisco Telecommunication companies, such as Internet and cellular service providers, are seeing rapid and uncertain growth of traffic routed through their networks. It has become a challenge for these companies to make optimal decisions for equipment purchase that simultaneously satisfy the uncertain future demand while minimizing investment cost. This paper presents a decision-making framework for installing the required equipment into the networks while in the uncertain environment. The framework is based on new multi-stage stochastic programming mathematical models that capture the complexity of the individual Central Office (CO) decision-making process. The models are solved using the on-line NEOS server. Two examples are presented to illustrate the procedure. The optimization model also addresses the equipment pricing problem, i.e., what premium is worth paying for shorter installation times.
• Regularization using a Parameterized Trust Region SubproblemOleg Grodzevich, Henry WolkowiczTo appear in Mathematical Programming Series B, Special Issue

2005

• On the Semidefinite Programming Relaxation of the Bin Packing ProblemOleg GrodzevichResearch Project Paper, University of Waterloo, 2005
• Regularization using a Parameterized Trust Region SubproblemOleg Grodzevich, Henry WolkowiczPoster Presentation, MITACS 2005 Conference in Calgary, AB

2004

• Regularization using a Parameterized Trust Region SubproblemOleg Grodzevich, supervisor: Henry WolkowiczMaster's Thesis, University of Waterloo, Combinatorics & Optimization, 2004 We present a new method for regularization of ill-conditioned problems that extends the traditional trust-region approach. Ill-conditioned problems arise, for example, in image restoration or mathematical processing of medical data, and involve matrices that are very ill-conditioned. The method makes use of the L-curve and L-curve maximum curvature criterion as a strategy recently proposed to find a good regularization parameter. We describe the method and show its application to an image restoration problem. We also provide a MATLAB code for the algorithm. Finally, a comparison to the CGLS approach is given and analyzed, and future research directions are proposed.

2003

• Introduction to Stochastic ProgrammingTalk given at Graduate Students Seminar, University of Waterloo, 2003
• Broadband and IP: Modelling, Scheduling, and OptimizationOleg Grodzevich, Hua Wei, Henry WolkowiczTechnical Report, University of Waterloo, 2001, CORR 2001-in progress