Linear and Nonlinear Programming
Description
David G. Luenberger received his B.S. degree from the California Institute of Technology and his M.S. and Ph.D. degrees from Stanford University, all in Electrical Engineering. Since 1963 he has served on the faculty of Stanford University. He helped found the Department of Engineering-Economic Systems, which have since become the Department of Management Science and Engineering, where his is currently a professor.
He is a Member of the National Academy of Engineering (2008) and has received e.g. the Bode Lecture Prize of the Control Systems Society (1990), the Oldenburger Medal of the American Society of Mechanical Engineers (1995), and the Expository Writing Award of the Institute of Operations Research and Management Science (1999). He is a Fellow of the Institute of Electrical and Electronic Engineers (since 1975).
Yinyu Ye
is currently the Kwoh-Ting Li Professor in the School of Engineering at the Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering. He received his B.S. degree in System Engineering from Huazhong University of Science and Technology, China, and his M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. He is an INFORMS (The Institute for Operations Research and The Management Science). Fellow since 2012, and has received several academic awards including: the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the 2015 SPS Signal Processing Magazine Best Paper Award, the winner of the 2014 SIAM Optimization Prize awarded (every three years), the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization (every three years), the inaugural 2006 Farkas Prize on Optimization, the 2009 IBM Faculty Award.
More details
Other editions
Additional editions
Previous edition
Persons
David G. Luenberger received his B.S. degree from the California Institute of Technology and his M.S. and Ph.D. degrees from Stanford University, all in Electrical Engineering. Since 1963 he has served on the faculty of Stanford University. He helped found the Department of Engineering-Economic Systems, which have since become the Department of Management Science and Engineering, where his is currently a professor.
He is a Member of the National Academy of Engineering (2008) and has received e.g. the Bode Lecture Prize of the Control Systems Society (1990), the Oldenburger Medal of the American Society of Mechanical Engineers (1995), and the Expository Writing Award of the Institute of Operations Research and Management Science (1999). He is a Fellow of the Institute of Electrical and Electronic Engineers (since 1975).
Yinyu Ye is currently the Kwoh-Ting Li Professor in the School of Engineering at the Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering. He received his B.S. degree in System Engineering from Huazhong University of Science and Technology, China, and his M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. He is an INFORMS (The Institute for Operations Research and The Management Science). Fellow since 2012, and has received several academic awards including: the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the 2015 SPS Signal Processing Magazine Best Paper Award, the winner of the 2014 SIAM Optimization Prize awarded (every three years), the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization (every three years), the inaugural 2006 Farkas Prize on Optimization, the 2009 IBM Faculty Award.
Content
1. Introduction.- Part I: Linear Programming.- 2. Basic Properties of Linear Programs.- 3. Duality and Complementarity.- 4. The Simplex Method.- 5. Interior-Point Methods.- 6. Conic Linear Programming.- Part II: Unconstrained Problems.- 7. Basic Properties of Solutions and Algorithms.- 8. Basic Descent Methods.- 9. Conjugate Direction Methods.- 10. Quasi-Newton Methods.- Part III: Constrained Optimization.- 11. Constrained Optimization Conditions.- 12. Primal Methods.- 13. Penalty and Barrier Methods.- 14. Local Duality and Dual Methods.- 15. Primal-Dual Methods.
