Titlebook: Geometric Algorithms and Combinatorial Optimization; Martin Gr?tschel,László Lovász,Alexander Schrijver Book 19881st edition Springer-Verl

使困惑

Conjuction

https://doi.org/10.1007/978-0-387-93840-0ction together with polyhedral information about these problems can be used to design polynomial time algorithms. In this chapter we give an overview about combinatorial optimization problems that are solvable in polynomial time. We also survey important theorems that provide polyhedral descriptions

ethnology

Disability Culture and Community Performancegraphs. (Alternative names for this problem used in the literature are vertex packing, or coclique, or independent set problem.) Our basic technique will be to look for various classes of inequalities valid for the stable set polytope, and then develop polynomial time algorithms to check if a given

歡笑

Syrus Ware,Joan Ruzsa,Giselle Diasny combinatorial theorems and problems, submodularity is involved, in one form or another, and submodularity often plays an essential role in a proof or an algorithm. Moreover, analogous to the fast methods for convex function minimization, it turns out that submodular functions can also be minimize

CRANK

https://doi.org/10.1007/978-3-642-97881-4Basis Reduction in Lattices; Basisreduktion bei Gittern; Combinatorics; Convexity; Ellipsoid Method; Elli

鈍劍

有毒

,Publications: Autumn 1832–Spring 1839,Convex sets and convex functions are typical objects of study in mathematical programming, convex analysis, and related areas. Here are some key questions one encounters frequently:

煞費(fèi)苦心

Mathematical Preliminaries,This chapter summarizes mathematical background material from linear algebra, linear programming, and graph theory used in this book. We expect the reader to be familiar with the concepts treated here. We do not recommend to go thoroughly through all the definitions and results listed in the sequel — they are mainly meant for reference.