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Combinatorial Optimization: Algorithms and
Combinatorial Optimization: Algorithms and

Combinatorial Optimization: Algorithms and Complexity by Christos H. Papadimitriou, Kenneth Steiglitz

Combinatorial Optimization: Algorithms and Complexity

Download Combinatorial Optimization: Algorithms and Complexity

Combinatorial Optimization: Algorithms and Complexity Christos H. Papadimitriou, Kenneth Steiglitz ebook
ISBN: 0486402584, 9780486402581
Publisher: Dover Publications
Format: djvu
Page: 513

Black-box optimization, oracle complexity. And Combinatorial Optimization INSTRUCTOR: Daya Gaur CLASS TIMES: Tuesday/Thursday 1:40 pm - 2:55 pm. In the recent post we discussed the question whether Microsoft Excel is a viable platform for developing and testing models and algorithms for complex combinatorial optimization problems. Computer Science > Data Structures and Algorithms By using OWA, the traditional min-max approach to combinatorial optimization problems with uncertain costs, often regarded as too conservative, can be generalized. This is the theory of black-box optimization. Search methods and combinatorial optimization techniques are not isolated from this phenomenon, as bigger computing power means the ability to attack more complex combinatorial problems. The computational complexity and approximability of the problem of minimizing OWA for the considered class of problems are investigated and some new positive and negative results in this area are provided. In the last years The next challenge is to devise efficient techniques and algorithms for massively parallel computers with tens or hundreds of thousands of cores in the form of heterogeneous hybrid systems based on both multi-core processors and GPUs. And it also naturally leads to algorithms that work in linear time, and which are thus well-suited for large-scale optimization. Rule appears on page 188 of Saul Gass's book, Linear Programming: Methods and Applications, 5th ed., 1985, taken from the version that appears in Papadimitriou and Steiglitz's book Combinatorial Optimization: Algorithms and Complexity,1982. Now that George had formulated a mathematical model for linear optimization, had discovered an efficient algorithm, and had solved some realistic problems with it, how should his work be communicated to the world? OBJECTIVE: To understand what can and cannot be achieved by computation especially by efficient computation. TOPICS: • Complexity theory • NP-completeness • Combinatorial algorithms • Approximation algorithms • Other topics depending on the interests in the class and time permitting. A background in computer science or mathematics (preferably with a specialization in one of the following topics: combinatorial optimization, discrete mathematics, approximation algorithms and computational complexity).

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