Sums of Random Symmetric Matrices and Applications

Let B_i be deterministic symmetric m\times m matrices, and \xi_i be independent random scalars with zero mean and “of order of one” (e.g., \xi_i are Gaussian with zero mean and unit standard deviation). We are interested in conditions for the “typical norm” of the random matrix S_N = \xi_1B_1+…+\xi_NB_N to be of order of 1. … Read more

Complex Quadratic Optimization and Semidefinite Programming

In this paper we study the approximation algorithms for a class of discrete quadratic optimization problems in the Hermitian complex form. A special case of the problem that we study corresponds to the max-3-cut model used in a recent paper of Goemans and Williamson. We first develop a closed-form formula to compute the probability of … Read more

Faster approximation algorithms for packing and covering problems

We adapt a method due to Nesterov so as to obtain an algorithm for solving block-angular fractional packing or covering problems to relative tolerance epsilon, while using a number of iterations that grows polynomially in the size of the problem and whose dependency on epsilon is proportional to 1/epsilon. Citation CORC report TR-2004-09, Computational Optimization … Read more

Approximate fixed-rank closures of set covering problems

We show that for any fixed rank, the closure of a set covering problem (and related problems) can be approximated in polynomial time — we can epsilon-approximate any linear program over the closure in polynomial time. Citation CORC report TR-2003-01, Computational Optimization Research Center, Columbia University Article Download View Approximate fixed-rank closures of set covering … Read more

On cost matrices with two and three distinct values of Hamiltonian paths and cycles

Polynomially testable characterization of cost matrices associated with a complete digraph on $n$ nodes such that all the Hamiltonian cycles (tours) have the same cost is well known. Tarasov~\cite{TARA81} obtained a characterization of cost matrices where tour costs take two distinct values. We provide a simple alternative characterization of such cost matrices that can be … Read more

Batched Bin Packing

We introduce and study the batched bin packing problem (BBPP), a bin packing problem in which items become available for packing incrementally, one batch at a time. A batched algorithm must pack a batch before the next batch becomes known. A batch may contain several items; the special case when each batch consists of merely … Read more

Introduction to Domination Analysis

In the recently published book on the Traveling Salesman Problem, half of Chapter 6 is devoted to domination analysis (DA) of heuristics for the Traveling Salesman Problem. Another chapter (in preparation) is a detailed overview of the whole area of DA. Both chapters are of considerable length. The purpose of this paper is to give … Read more

A Multi-Exchange Local Search Algorithm for the Capacitated Facility Location Problem

We present a multi-exchange local search algorithm for approximating the capacitated facility location problem (CFLP), where a new local improvement operation is introduced that possibly exchanges multiple facilities simultaneously. We give a tight analysis for our algorithm and show that the performance guarantee of the algorithm is between $3+2\sqrt{2}-\epsilon$ and $3+2\sqrt{2}+\epsilon$ for any given constant … Read more

On-Line Scheduling to Minimize Average Completion Time Revisited

We consider the scheduling problem of minimizing the average weighted completion time on identical parallel machines when jobs are arriving over time. For both the preemptive and the nonpreemptive setting, we show that straightforward extensions of Smith’s ratio rule yield smaller competitive ratios than the previously best-known deterministic on-line algorithms. Citation Working Paper 4435-03, Sloan … Read more

Domination analysis for minimum multiprocessor scheduling

Let $P$ be a combinatorial optimization problem, and let $A$ be an approximation algorithm for $P$. The domination ratio $\domr(A,s)$ is the maximal real $q$ such that the solution $x(I)$ obtained by $A$ for any instance $I$ of $P$ of size $s$ is not worse than at least the fraction $q$ of the feasible solutions … Read more