<p>This book contains refereed papers which were presented at the 34th Workshop of the International School of Mathematics "G. Stampacchia,β the International Workshop on Optimization and Control with Applications. The book contains 28 papers that are grouped according to four broad topics: duality
Optimization and Control with Applications
β Scribed by A.M. Bagirov, A.M. Rubinov (auth.), Liqun Qi, Koklay Teo, Xiaoqi Yang (eds.)
- Publisher
- Springer US
- Year
- 2005
- Tongue
- English
- Leaves
- 586
- Series
- Applied Optimization 96
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Subjects
Optimization
π SIMILAR VOLUMES
<p>This book contains refereed papers which were presented at the 34th Workshop of the International School of Mathematics "G. Stampacchia,β the International Workshop on Optimization and Control with Applications. The book contains 28 papers that are grouped according to four broad topics: duality
This book contains refereed papers which were presented at the 34th Workshop of the International School of Mathematics "G. Stampacchia,β the International Workshop on Optimization and Control with Applications. The book contains 28 papers that are grouped according to four broad topics: duality and
This sound introduction to classical and modern control theory concentrates on fundamental concepts. Employing the minimum of mathematical elaboration, it investigates the many applications of control theory to varied and important present-day problems, e.g. economic growth, resource depletion, dise
<DIV> <DIV>This sound introduction to classical and modern control theory concentrates on fundamental concepts. Employing the minimum of mathematical elaboration, it investigates the many applications of control theory to varied and important present-day problems, e.g. economic growth, resource dep
<p><P>Because the theoretical part of the book is based on the calculus of variations, the exposition is very transparent and requires mostly a trivial mathematical background. In the case of open-loop optimal control, this leads to Pontryaginβs Minimum Principle and, in the case of closed-loop opti