Here I will present an introduction to the results that have been recently obtained in constraint optimization of random problems using statistical mechanics techniques. After presenting the general results, in order to simplify the presentation I will describe in details the problems related to the coloring of a random graph. (c) 2006 Elsevier B.V. All rights reserved
Probabilistic analysis for metric optimization problems has mostly been conducted on random Euclidea...
This thesis is divided in two parts. The first presents an overview of known results in statistical ...
For a number of random constraint satisfaction problems, such as random k-SAT and random graph/hyper...
Optimization is fundamental in many areas of science, from computer science and information theory t...
AbstractRecently, it has been recognized that phase transitions play an important role in the probab...
The problem of vertex coloring in random graphs is studied using methods of statistical physics and ...
We consider optimization problems on complete graphs with edge weights drawn independently from a fi...
We study constraint satisfaction problems on the so-called planted random ensemble. We show that for...
10 pages, Proceedings of the International Workshop on Statistical-Mechanical Informatics 2007, Kyot...
Optimization problems arising in practice involve random model parameters. This book features many i...
Deterministic optimization models are usually formulated as problems of mini-mizing or maximizing a ...
The deterministic theory of graphs and networks is used successfully in cases where no random compon...
Random convex programs (RCPs) are convex optimization problems subject to a finite number of constra...
For many random constraint satisfaction problems, by now there exist asymptotically tight estimates ...
Random constraint satisfaction problems have been on the agenda of various sciences such as discrete...
Probabilistic analysis for metric optimization problems has mostly been conducted on random Euclidea...
This thesis is divided in two parts. The first presents an overview of known results in statistical ...
For a number of random constraint satisfaction problems, such as random k-SAT and random graph/hyper...
Optimization is fundamental in many areas of science, from computer science and information theory t...
AbstractRecently, it has been recognized that phase transitions play an important role in the probab...
The problem of vertex coloring in random graphs is studied using methods of statistical physics and ...
We consider optimization problems on complete graphs with edge weights drawn independently from a fi...
We study constraint satisfaction problems on the so-called planted random ensemble. We show that for...
10 pages, Proceedings of the International Workshop on Statistical-Mechanical Informatics 2007, Kyot...
Optimization problems arising in practice involve random model parameters. This book features many i...
Deterministic optimization models are usually formulated as problems of mini-mizing or maximizing a ...
The deterministic theory of graphs and networks is used successfully in cases where no random compon...
Random convex programs (RCPs) are convex optimization problems subject to a finite number of constra...
For many random constraint satisfaction problems, by now there exist asymptotically tight estimates ...
Random constraint satisfaction problems have been on the agenda of various sciences such as discrete...
Probabilistic analysis for metric optimization problems has mostly been conducted on random Euclidea...
This thesis is divided in two parts. The first presents an overview of known results in statistical ...
For a number of random constraint satisfaction problems, such as random k-SAT and random graph/hyper...
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