This paper presents the Facet Generation Procedure (FGP) for solving 0/1 integer programs. The FGP seeks to identify a hyperplane that represents a facet of an underlying polytope to cut off the fractional solution to the linear programming relaxation of the integer programming problem. A set of standard problems is used to provide insight into the computational characteristics of the procedure.

We prove that any minimal valid function for the k-dimensional infinite group relaxation that is continuous piecewise linear with at most k+ 1 slopes and does not factor through a linear map with non-trivial kernel is extreme. This generalizes a theorem of Gomory and Johnson for k = 1, and Cornuéjols and Molinaro for k = 2.

We investigate the relaxation of long-tailed distributions under stochastic dynamics that do not support such tails. Linear relaxation is found to be a borderline case in which long tails are exponentially suppressed in time but not eliminated. Relaxation stronger than linear suppresses long tails immediately, but may lead to strong transient peaks in the probability distribution. We also find ...

The class of POPs (Polynomial Optimization Problems) over cones covers a wide range of optimization problems such as 0-1 integer linear and quadratic programs, nonconvex quadratic programs and bilinear matrix inequalities. This paper presents a new framework for convex relaxation of POPs over cones in terms of linear optimization problems over cones. It provides a unified treatment of many exis...

We consider the case of a scalar field, the inflaton, coupled to both lighter scalars and fermions, and the study the relaxation of the inflaton via particle production in both the linear and non-linear regimes. This has an immediate application to the reheating problem in inflationary universe models. The linear regime analysis offers a rationale for the standard approach to the reheating prob...

We study properties of systems of linear constraints that are minimally infeasible with respect to some subset S of constraints (i.e. systems that are infeasible, but become feasible upon removal of any constraint in S). We then apply these results and a theorem of Conforti, Cornuéjols, Kapoor, and Vušković, to a class of 0, 1 matrices, for which the linear relaxation of the set partitioning po...

Burer has shown that completely positive relaxations of nonconvex quadratic programs with nonnegative and binary variables are exact when the binary variables satisfy a so-called key assumption. Here we show that introducing binary variables to obtain an equivalent problem that satisfies the key assumption will not improve the semidefinite relaxation, and only marginally improve the doubly nonn...

In this paper, we apply the  homotopy analysis method (HAM) for solving fuzzy  linear systems and present  the necessary and sufficient conditions for the convergence of series solution obtained via the HAM. Also, we present a new criterion for choosing a proper value of convergence-control parameter $hbar$ when the HAM is applied to linear system of equations. Comparisons are made between the ...

In this paper, we address a new integration of column generation and Lagrangian relaxation for solving flowshop scheduling problems to minimize the total weighted tardiness. In the proposed method, the initial columns are generated by using near-optimal dual variables for linear programming relaxation of Dantzig-Wolfe decomposition derived by the Lagrangian relaxation method. The column generat...

This paper is concerned with the solvability and waveform relaxation methods of linear variable-coefficient differential-algebraic equations (DAEs). Most of the previous works have been focused on linear variable-coefficient DAEs with smooth coefficients and data, yet no results related to the convergence rate of the corresponding waveform relaxation methods has been obtained. In this paper, we...