期刊
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
卷 1, 期 1, 页码 99-122出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/jimo.2005.1.99
关键词
stochastic mathematical program with equilibrium constraints; here-and-now decision problem; stationarity; sub differential; convergence
We consider a class of stochastic mathematical programs with equilibrium constraints (SMPECs), in which all decisions are required to be made here-and-now, before a random event is observed. We show that this kind of SMPEC plays a very important role in practice. In order to develop effective algorithms, we first give some reformulations of the SMPEC and then, based on these reformulations, we propose a smoothed penalty approach for solving the problem. A comprehensive convergence theory is also included.
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