This rigorous introduction to the fundamental ideas of convexity and their use in optimization offers a unifying approach for both discrete and continuous applications. Students and researchers in optimization, operations research, computer science, and applied mathematics will appreciate the book's 300+ exercises and coverage of new developments.
This rigorous introduction to the fundamental ideas of convexity and their use in optimization offers a unifying approach for both discrete and continuous applications. Students and researchers in optimization, operations research, computer science, and applied mathematics will appreciate the book's 300+ exercises and coverage of new developments.
Amitabh Basu is Professor of Applied Mathematics and Statistics at Johns Hopkins University. He has received the NSF CAREER award and the Egon Balas Prize from the INFORMS Optimization Society. He serves on the editorial boards of 'Mathematics of Operations Research,' 'Mathematical Programming,' 'SIAM Journal on Optimization,' and the 'MOS-SIAM Series on Optimization.'
Inhaltsangabe
1. Preliminaries Part I. Structural Aspects: 2. Convex sets 3. Convex functions 4. Geometry of numbers Part II. Optimization: 5. Ingredients of mathematical optimization 6. Complexity of convex optimization with integer variables 7. Certificates and duality Hints to selected exercises References Index.
1. Preliminaries Part I. Structural Aspects: 2. Convex sets 3. Convex functions 4. Geometry of numbers Part II. Optimization: 5. Ingredients of mathematical optimization 6. Complexity of convex optimization with integer variables 7. Certificates and duality Hints to selected exercises References Index.
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