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Jinhai Guo

Publications and source records attributed to Jinhai Guo.

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Multiparametric analysis of conic linear optimization based on the lift-and-project procedure

We study how the lift-and-project procedure applies to the multiparametric analysis of conic linear optimization (CLO) problems. We first introduce the concept of a pair of primal and dual conic representable sets and define the set-valued mappings between them. We then explore a novel kind of duality of mpCLOs, which allows us to generalize as well as treat previous results for the mulitparametric analysis in a unified framework. In particular, we discuss the behavior of the optimal partition of a conic representable set. This leads to the invariant region decomposition of a conic representable set that is more general than the known results in the literatures. Finally, we study the properties of the optimal objective values as a function of that parametric vectors. All results are corroborated by examples having correlation.

math.OC

The existence of a strongly polynomial time simplex algorithm for linear programs

It is well known that the most challenging question in optimization and discrete geometry is whether there is a strongly polynomial time simplex algorithm for linear programs (LPs). This paper gives a positive answer to this question by using the parameter analysis technique presented by us (arXiv:2006.08104). We show that there is a simplex algorithm whose number of pivoting steps does not exceed the number of variables of a LP problem.

math.OC

The optimal partition for multiparametric semialgebraic optimization

In this paper we investigate the optimal partition approach for multiparametric conic linear optimization (mpCLO) problems in which the objective function depends linearly on vectors. We first establish more useful properties of the set-valued mappings early given by us (arXiv:2006.08104) for mpCLOs, including continuity, monotonicity and semialgebraic property. These properties characterize the notions of so-called linearity and nonlinearity subsets of a feasible set, which serve as stability regions of the partition of a conic (linear inequality) representable set. We then use the arguments from algebraic geometry to show that a semialgebraic conic representable set can be decomposed into a union of finite linearity and/or nonlinearity subsets. As an application, we investigate the boundary structure of the feasible set of generic semialgebraic mpCLOs and obtain several nice structural results in this direction, especially for the spectrahedon.

math.OC