[專題演講] 【9月17日】Vo Si Trong Long / Qualitative Analysis and Adaptive Boosted DCA for Generalized k-Center and Multi-Source Weber Problems

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Qualitative Analysis and Adaptive Boosted DCA for Generalized k-Center and Multi-Source Weber Problems

Time: Sep. 17 (Wed.) 14:20-15:10
Venue: M212, Gongguan Campus, NTNU

Prof. Vo Si Trong Long

Mathematics and Computer Science, University of Science,
Vietnam National University, Ho Chi Minh City

This talk has two primary objectives. First, we investigate fundamental qualitative properties of the generalized k-center and multi-source Weber problems formulated using the Minkowski gauge function. This includes proving the existence of global optimal solutions, demonstrating the compactness of the solution set, and establishing optimality conditions for these solutions. Second, we apply Nesterov’s smoothing and the adaptive Boosted Difference of Convex functions Algorithm (BDCA) to solve both the unconstrained and constrained versions of the generalized multi-source Weber problems.

Keywords: Generalized multi-source Weber problem, Nesterov’s smoothing, DCA, boosted DCA.