We consider the problem of scheduling a set of tasks related by precedence constraints to a set of processors, so as to minimize their makespan. Each task has to be assigned to a unique processor and no preemption is allowed. A new integer programming formulation of the problem is given and strong valid inequalities are … Read more
We propose a new method for non-bijective graph matching for model-based pattern recognition. We formulate the search for the best correspondence between a model and an over-segmented image as a new combinatorial optimization problem, defined by the relational attributed graphs representing the model and the image where recognition has to be performed, together with the … Read more
A phylogenetic tree relates taxonomic units, based on their similarity over a set of characters. We propose a new genetic algorithm for the problem of building a phylogenetic tree under the parsimony criterion. This genetic algorithm makes use of an innovative optimized crossover strategy which is an extension of the path-relinking intensification technique originaly proposed … Read more
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. CitationWorking Paper 4435-03, Sloan School … Read more
The low-rank semidefinite programming problem (LRSDP_r) is a restriction of the semidefinite programming problem (SDP) in which a bound r is imposed on the rank of X, and it is well known that LRSDP_r is equivalent to SDP if r is not too small. In this paper, we classify the local minima of LRSDP_r and … Read more
Representation of a given nonnegative multivariate polynomial in terms of a sum of squares of polynomials has become an essential subject in recent developments of sums of squares optimization and SDP (semidefinite programming) relaxation of polynomial optimization problems. We disscuss effective methods to obtain a simpler representation of a “sparse” polynomial as a sum of … Read more
In this paper we use facets of mixed-integer sets with two and three variables to derive valid inequalities for integer sets defined by a single equation. These inequalities also define facets of the master cyclic group polyhedron of Gomory. Facets of this polyhedron give strong valid inequalities for general mixed-integer sets, such as the well-known … Read more
We give an algorithm for the following problem: given a graph $G=(V,E)$ with edge-weights and a nonnegative integer $k$, find a minimum cost set of edges that contains $k$ disjoint spanning trees. This also solves the following {\it reinforcement problem}: given a network, a number $k$ and a set of candidate edges, each of them … Read more
We propose a dynamic version of the bundle method to get approximate solutions to semidefinite programs with a nearly arbitrary number of linear inequalities. Our approach is based on Lagrangian duality, where the inequalities are dualized, and only a basic set of constraints is maintained explicitly. This leads to function evaluations requiring to solve a … Read more
Decomposition algorithms such as Lagrangian relaxation and Dantzig-Wolfe decomposition are well-known methods that can be used to generate bounds for mixed-integer linear programming problems. Traditionally, these methods have been viewed as distinct from polyhedral methods, in which bounds are obtained by dynamically generating valid inequalities to strengthen the linear programming relaxation. Recently, a number of … Read more