We study a perishable inventory system that requires to maintain a minimum inventory volume at all times, where the minimum amount in the constraint is significant with respect to regular market demand and the traditional Economic Manufacturing Quantity (EMQ) models do not suffice. The problem is motivated by applications in homeland security, which are related to the management of pharmaceutic...

We study a perishable inventory system that requires to maintain a minimum inventory volume at all times, where the minimum amount in the constraint is significant with respect to regular market demand and the traditional Economic Manufacturing Quantity (EMQ) models do not suffice. The problem is motivated by applications in homeland security, which are related to the management of pharmaceutic...

This note studies the learnability of ordered binary decision diagrams (obdds). We give a polynomial-time algorithm using membership and equivalence queries that nds the minimum obdd for the target respecting a given ordering. We also prove that both types of queries and the restriction to a given ordering are necessary if we want minimality in the output, unless P=NP. If learning has to occur ...

Most companies are under heavy time and resource constraints when it comes to testing a software system. Test prioritization technique(s) allows the most useful tests to be executed first, exposing faults earlier in the testing process. Thus makes software testing more efficient and cost effective by covering maximum faults in minimum time. But test case prioritization is not an easy and straig...

For sparse QR factorization, nding a good column ordering of the matrix to be factorized, is essential. Both the amount of ll in the resulting factors, and the number of oating-point operations required by the factorization, are highly dependent on this ordering. A suitable column ordering of the matrix A is usually obtained by minimum degree analysis on A T A. The objective of this analysis is...

When performing sparse matrix factorization, the ordering of matrix rows and columns has a dramatic impact on the factorization time. This paper describes an approach to the reordering problem that produces signiicantly better orderings than previous methods. The algorithm is a hybrid of nested dissection and minimum degree ordering, and combines an assortment of algorithmic techniques.

In recent years, nested dissection has grown in popularity as the method of choice for computing a pivot sequence for use with a sparse direct symmetric solver. This is particularly true for very large problems. For smaller problems, minimum degree based algorithms often produce orderings that lead to sparser matrix factors. Furthermore, minimum degree orderings are frequently significantly che...

In this paper those graphs are studied for which a so-called strong ordering of the vertex set exists. This class of graphs, called strongly orderable graphs, generalizes the strongly chordal graphs and the chordal bipartite graphs in a quite natural way. We consider two characteristic elimination orderings for strongly orderable graphs, one on the vertex set and the second on the edge set, and...

For digraphs G and H, a homomorphism of G to H is a mapping f : V (G)→V (H) such that uv ∈ A(G) implies f(u)f(v) ∈ A(H). If moreover each vertex u ∈ V (G) is associated with costs ci(u), i ∈ V (H), then the cost of a homomorphism f is ∑ u∈V (G) cf(u)(u). For each fixed digraph H, the minimum cost homomorphism problem for H, denoted MinHOM(H), is the following problem. Given an input digraph G, ...

In this paper we consider finding solutions for problems represented using AND/OR graphs, which contain tasks that can fail when executed. In our setting each node represent an atomic task which is associated with a failure probability and a rollback penalty. This paper reports the following contributions (a) an algorithm for finding the optimal ordering of the atomic tasks in a given solution ...