We discuss the variability in the performance of multiple runs of Mixed Integer Linear solvers, and we concentrate on the one deriving from the use of different optimal bases of the Linear Programming relaxations. We propose a new algorithm exploiting more than one of those bases and we show that different versions of the algorithm can be used to stabilize and improve the performance of the sol...

The RF phases, defined as the phases between the crests of the RF accelerating voltages and the accelerated beam, must be controlled within a few degrees in the linac of the SLAC Linear Collider (SLC). Changes in the RF phases not only affect the available acceleration but more importantly modify the dynamics of the accelerated beam, e.g. the beam optics. Precision phase control is therefore cr...

This paper develops a method for finding the whole set of efficient points of a multiobjective linear problem. Two algorithms are presented; the first one describes the set of all efficient vertices and all efficient rays of the constraint polyhedron, while the second one generates the set of all efficient faces. The method has been tested on several examples for which numerical results are rep...

A mathematical programming approach to deal with the global configuration of resource constraints is presented. A specialized parametric programming algorithm to obtain the pareto set for the biobjective problem that appears to deal with the global configuration for 0-1-Integer Linear Programing problems is presented and implemented. Computational results for Multiconstrained Knapsack problems ...

In this study we consider a multiobjective integer linear stochastic programming problem with individual chance constraints. We assume that there is randomness in the right-hand sides of the constraints only and that the random variables are normally distributed. Some stability notions for such problem are characterized. An auxiliary problem is discussed and an algorithm as well as an illustrat...

We proposed a pivot algorithm using the affine-scaling technique. It produces a sequence of interior points as well as a sequence of vertices, until reaching an optimal vertex. We report preliminary but favorable computational results obtained with a dense implementation of it on a set of standard Netlib test problems.

We identify a novel class of distributed optimization problems, namely a networked version of abstract linear programming. For such problems we propose distributed algorithms for networks with various connectivity and/or memory constraints. Finally, we show how a suitable target localization problem can be tackled through appropriate linear programs.