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"Linear and Nonlinear Equations Programming in Mathematics" is considered a classic textbook in mathematics and optimization. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as a means for learning existing material and for developing new results. One major insight of this type is the connection between the purely analytical character of an optimization problem, expressed perhaps by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. Mohammad and Chen, has written…mehr

Produktbeschreibung
"Linear and Nonlinear Equations Programming in Mathematics" is considered a classic textbook in mathematics and optimization. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as a means for learning existing material and for developing new results. One major insight of this type is the connection between the purely analytical character of an optimization problem, expressed perhaps by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. Mohammad and Chen, has written this book and chapter material on a number of these areas including Interior Point Methods. This book is designed for either self-study by two PhD students in (Management Science and Engineering, School of Economics and Management, Nanjing University of Science and Technology, Nanjing, Jiangsu, China) also, professionals or classroom work at the undergraduate or graduate level for technical students. Like the field of optimization itself, which involves many classical disciplines, the book should be useful to system analysts, operations researchers, management scientists, and other specialists.
Autorenporträt
Das vorliegende Buch, das Sie jetzt in Händen halten, ist das Ergebnis vieler Bemühungen dieser Doktoranden und Professoren verschiedener Universitäten auf dem chinesischen Festland. Geschrieben wurde es von "Mohammad Heydari, Yufan Shang, Zheng Yuxi, Kin Keung Lai, Zhou Xiaohu und Oksana Shatska".