B-347 Towards the Implementation of Successive Convex Relaxation Method for Noncon- vex Quadratic Optimization Problems
نویسندگان
چکیده
Recently Kojima and Tun cel 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 nite number of linear programs, several important implementation problems remain unsolved. In this paper we discuss these issues, present practically implementable algorithms and report numerical results.
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