MSThE43
Optimization algorithms and application  Part III of V
For Part I, see MSThBC43
For Part II, see MSThD43
For Part IV, see MSFrD43
For Part V, see MSFrE43
Date: August 13
Time: 16:0018:00
Room: 41
(Note: Click title to show the abstract.)
Organizer:
Wen, Zaiwen (Peking Univ.)
Yuan, Yaxiang (Inst. of Computational Mathematics & Scientific/Engineering Computing)
Xia, Yong (Beihang Univ.)
Abstract: This minisymposium consists 5 sessions. It highlights recent advances in theory, algorithms and applications of mathematical optimization on solving huge problems that are intractable for current methods.
MSThE431
16:0016:30
On the Linear Convergence Rate of a Generalized Proximal Point Algorithm
Tao, Min (Nanjing Univ.)
Yuan, Xiaoming (Hong Kong Baptist Univ.)
Abstract: We consider a generalized PPA in the generic setting of finding a zero point of a maximal monotone operator, and show that the condition proposed by Rockafellar can also sufficiently ensure the linear convergence rate for this generalized PPA. Both the exact and inexact versions of this generalized PPA are discussed.
MSThE432
16:3017:00
A New Look at the Reweighted L1 Minimization
LI, Donghui (South China Normal Univ.)
Abstract: We reformulate the Lpregularization problem to a smooth
constrained optimization problem. Based on the reformulation,
we propose a sequence L1regularization method to solve the problem.
The method is motivated by a sequential quadratic
programming (SQP) method for
solving a smooth constrained optimization reformulation to the problem.
We find that the method is indeed a reweighted L1 minimization method.
It then gives a new look at the reweighted L1minimization method.
MSThE433
17:0017:30
Some optimization problems in petrochemical industry
Dai, YuHong (Chinese Acad. of Sci.)
Abstract: In this talk, we will discuss two optimization problems applied in petrochemical industry. Firstly, the petroleum mixture problem can be formed into a bilinear problem. We managed to settle it by nonmonotone sucessive linear programming (NMSLP). Numerical experiments show that NMSLP is competive with the commecial solver PIMS in both solution quality and CPU time. Secondly, we introduce the utility problem, which is a mixed integer nonlinear problem. We exploit the structure and put forward a heuristic method. Numerical results by data in real industry are shown.
MSThE434
17:3018:00
An inexact alternating direction algorithm for separable convex optimization.
Zhang, Hongchao (Lousiana State Univ.)
Abstract: We will introduce an inexact alternating direction algorithm with variable stepsize for solving separable convex
optimization. This algorithm generalizes the Bregman operator splitting algorithm with variable stepsiz (BOSVS) to the multiblock case and allows to solve the convex subproblems to an adaptive accuracy. Global convergence and some
preliminary numerical results will be discussed in this talk.
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Footnote: Code: TypeDateTimeRoom No.
Type : IL=Invited Lecture, SL=Special Lectures, MS=Minisymposia, IM=Industrial Minisymposia, CP=Contributed Papers, PP=Posters
Date: Mo=Monday, Tu=Tuesday, We=Wednesday, Th=Thursday, Fr=Friday
Time : A=8:309:30, B=10:0011:00, C=11:1012:10, BC=10:0012:10, D=13:3015:30, E=16:0018:00, F=19:0020:00, G=12:1013:30, H=15:3016:00
Room No.: TBA
