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Nonsmooth Approach to Optimization Problems with Equilibrium Constraints : Theory, Applications and Numerical Results by Jiři Outrata, Michal Kočvara, Jochem Zowe (auth.) is a nonfiction available to read on EtoBox.
What is Nonsmooth Approach to Optimization Problems with Equilibrium Constraints : Theory, Applications and Numerical Results about?
In the early fifties, applied mathematicians, engineers and economists started to pay c10se attention to the optimization problems in which another (lower-Ievel) optimization problem arises as a side constraint. One of the motivating factors was the concept of the Stackelberg solution in game theory, together with its economic applications. Other problems have been encountered in the seventies in natural sciences and engineering. Many of them are of practical importance and have been extensively studied, mainly from the theoretical point of view. Later, applications to mechanics and network design have lead to an extension of the problem formulation: Constraints in form of variation al inequalities and complementarity problems were also admitted. The term "generalized bi level programming problems" was used at first but later, probably in Harker and Pang, 1988, a different terminology was introduced: Mathematical programs with equilibrium constraints, or simply, MPECs. In this book we adhere to MPEC terminology. A large number of papers deals with MPECs but, to our knowledge, there is only one monograph (Luo et al. , 1997). This monograph concentrates on optimality conditions and n
Who reads Nonsmooth Approach to Optimization Problems with Equilibrium Constraints : Theory, Applications and Numerical Results?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Jiři Outrata, Michal Kočvara, Jochem Zowe (auth.)
- Publisher
- Springer US : Imprint : Springer
- Published
- 1998
- Language
- EN
- ISBN
- 9781441948045
- Category
- nonfiction
- Subjects
- Business, Programming, Computer Science
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