in Combinatorial Optimization April 8 , 2004 Lecture 16 Lecturer : Michel
نویسنده
چکیده
We now consider some examples of jump systems. Example 1. Let M be a matroid over a set S, |S| = n. We let each coordinate of Z correspond to an element of S, and let J ⊆ {0, 1}n be the set of characteristic functions for bases of M , J = {χB|B a basis of M}. Claim 1. The set J is a jump system. Proof. Let x and y be the respective characteristic vectors of two bases b1 and b2 of M . A step x from x to y corresponds to either: 1. Adding to b1 an element of b2 \ b1, or 2. Removing from b1 some element of b1 \ b2. ′ / Since all bases have the same size, the set corresponding to x will never be a basis, so x′ ∈ J . We thus require there to be some step x′′ from x to y such that x′′ ∈ J , i.e., such that the set corresponding to x′′ is a basis. In both cases, this is guaranteed by Basis Exchange (see lecture 11).
منابع مشابه
Linear programming Lecturer : Michel Goemans 1 Basics
Linear Programming deals with the problem of optimizing a linear objective function subject to linear equality and inequality constraints on the decision variables. Linear programming has many practical applications (in transportation, production planning, ...). It is also the building block for combinatorial optimization. One aspect of linear programming which is often forgotten is the fact th...
متن کاملLecture 6 — April 16 Lecturer
Last time, we introduced the task of hierarchical clustering, in which we aim to produce nested clusterings that reflect the similarity between clusters. This contrasts sharply with our former discussion of “flat” or structureless clustering methods like k-means which do not model relationships between clusters. In this lecture, we will continue our discussion of the standard model-free approac...
متن کامل8.438 Advanced Combinatorial Optimization 2 Iwata and Orlin's Algorithm
Given a finite set V with n elements, a function f : 2 → Z is submodular if for all X,Y ⊆ V , f(X ∪ Y ) + f(X ∩ Y ) ≤ f(X) + f(Y ). Submodular functions frequently arise in combinatorial optimization. For example, the cut function in a weighted undirected graph and the rank function of a matroid are both submodular. Submodular function minimization is the problem of finding the global minimum o...
متن کاملLecture 1 Polynomial Time Hierarchy April 1 , 2008 Lecturer : Paul Beame
We first define the classes in the polynomial-time hierarchy.
متن کاملMichel X . Goemans 7 . Lecture notes on the ellipsoid algorithm
The simplex algorithm was the first algorithm proposed for linear programming, and although the algorithm is quite fast in practice, no variant of it is known to be polynomial time. The Ellipsoid algorithm is the first polynomial-time algorithm discovered for linear programming. The Ellipsoid algorithm was proposed by the Russian mathematician Shor in 1977 for general convex optimization proble...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004