On linear programs with linear complementarity constraints

被引:0
|
作者
Jing Hu
John E. Mitchell
Jong-Shi Pang
Bin Yu
机构
[1] Market Analytics,Department of Mathematical Sciences
[2] Inc.,Department of Industrial and Enterprise Systems Engineering
[3] Rensselaer Polytechnic Institute,Department of Decision Sciences and Engineering Systems
[4] University of Illinois,undefined
[5] Rensselaer Polytechnic Institute,undefined
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关键词
Linear programs with linear complementarity constraints; Inverse programming; Hierarchical programming; Piecewise linear programming; Quantile minimization; Cross-validated support vector regression;
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摘要
The paper is a manifestation of the fundamental importance of the linear program with linear complementarity constraints (LPCC) in disjunctive and hierarchical programming as well as in some novel paradigms of mathematical programming. In addition to providing a unified framework for bilevel and inverse linear optimization, nonconvex piecewise linear programming, indefinite quadratic programs, quantile minimization, and ℓ0 minimization, the LPCC provides a gateway to a mathematical program with equilibrium constraints, which itself is an important class of constrained optimization problems that has broad applications. We describe several approaches for the global resolution of the LPCC, including a logical Benders approach that can be applied to problems that may be infeasible or unbounded.
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页码:29 / 51
页数:22
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