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1999 MCS Divisional Seminars & Colloquia |
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| Abstract | Recently Kojima and Tunccel proposed new successive convex relaxation methods and their localized-discretized variants for general nonconvex quadratic programs. Although an upper bound of the objective function value within a prior precision can be found theoretically by solving a finite number of linear programs, several important implementation problems remain unsolved. In this talk we discuss these issues, present practically implementable algorithms and report numerical results. |
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