Polyhedral aspects of a robust knapsack problem

While dealing with uncertainty in linear programs, the robust optimization framework proposed by Bertsimas and Sim appears as relevant. In particular, it can readily be extended for integer linear programming. This paper outlines the polyhedral impacts of this robust model for the 0-1 knapsack problem. It shows especially how the classical cover cuts can be … Read more

On a resource-constrained scheduling problem with application to distributed systems reconfiguration

This paper is devoted to the study of a resource-constrained scheduling problem which arises in relation to the operability of certain high availability real-time distributed systems. After a brief survey of the literature, we prove the NP-hardness of the problem and exhibit a few polynomial special cases. We then present a branch-and-bound algorithm for the … Read more

A branch-and-cut algorithm for a resource-constrained scheduling problem

This paper is devoted to the exact resolution of a strongly NP-hard resource-constrained scheduling problem, the Process Move Programming problem, which arises in relation to the operability of certain high availability real time distributed systems. Based on the study of the polytope defined as the convex hull of the incidence vectors of the admissible process … Read more

Approximate resolution of a resource-constrained scheduling problem

This paper is devoted to the approximate resolution of a strongly NP-hard resource-constrained scheduling problem which arises in relation to the operability of certain high availability real time distributed systems. We present an algorithm based on the simulated annealing metaheuristic and, building on previous research on exact resolution methods, extensive computational results demonstrating its practical … Read more

Packing and Partitioning Orbitopes

We introduce orbitopes as the convex hulls of 0/1-matrices that are lexicographically maximal sub ject to a group acting on the columns. Special cases are packing and partitioning orbitopes, which arise from restrictions to matrices with at most or exactly one 1-entry in each row, respectively. The goal of investigating these polytopes is to gain … Read more

Nonserial dynamic programming and local decomposition algorithms in discrete programming

One of perspective ways to exploit sparsity in the dependency graph of an optimization problem as J.N. Hooker stressed is nonserial dynamic programming (NSDP) which allows to compute solution in stages, each of them uses results from previous stages. The class of discrete optimization problems with the block-tree-structure matrix of constraints is considered. Nonserial dynamic … Read more

On forests, stable sets and polyhedras associated with clique partitions

Let $G=(V,E)$ be a simple graph on $n$ nodes. We show how to construct a partial subgraph $D$ of the line graph of $G$ satisfying the identity: $\overline \chi(G)+\alpha(D)=n$, where $\overline \chi(G)$ denotes the minimum number of cliques in a clique partition of $G$ and $\alpha(D)$ denotes the maximum size of a stable set of … Read more

On the p-median polytope of a special class of graphs

In this paper we consider a well known class of valid inequalities for the p-median and the uncapacitated facility location polytopes, the odd cycle inequalities. It is known that their separation problem is polynomially solvable. We give a new polynomial separation algorithm based on a reduction from the original graph. Then, we define a nontrivial … Read more

The p-median polytope of restricted Y-graphs

We further study the effect of odd cycle inequalities in the description of the polytopes associated with the p-median and uncapacitated facility location problems. We show that the obvious integer linear programming formulation together with the odd cycle inequalities completely describe these polytopes for the class of restricted Y-graphs. This extends our results for the … Read more

Global optimization by continuous GRASP

We introduce a novel global optimization method called Continuous GRASP (C-GRASP) which extends Feo and Resende’s greedy randomized adaptive search procedure (GRASP) from the domain of discrete optimization to that of continuous global optimization. This stochastic local search method is simple to implement, is widely applicable, and does not make use of derivative information, thus … Read more