A genetic algorithm for the phylogeny problem using an optimized crossover strategy based on path-relinking

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

A limited memory algorithm for inequality constrained minimization

A method for solving inequality constrained minimization problems is described. The algorithm is based on a primal-dual interior point approach, with a line search globalization strategy. A quasi-Newton technique (BFGS) with limited memory storage is used to approximate the second derivatives of the functions. The method is especially intended for solving problems with a large … Read more

Interior-Point Algorithms, Penalty Methods and Equilibrium Problems

In this paper we consider the question of solving equilibrium problems—formulated as complementarity problems and, more generally, mathematical programs with equilibrium constraints (MPEC’s)—as nonlinear programs, using an interior-point approach. These problems pose theoretical difficulties for nonlinear solvers, including interior-point methods. We examine the use of penalty methods to get around these difficulties, present an example … 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

A Homogeneous Model for $ and *$ Nonlinear Complementarity Problems

The homogeneous model for linear programs is an elegant means of obtaining the solution or certificate of infeasibility and has importance regardless of the method used for solving the problem, interior-point methods or other methods. In 1999, Andersen and Ye generalized this model to monotone complementarity problems (CPs) and showed that most of the desirable … Read more

Generalized Lagrangian Duals and Sums of Squares Relaxations of Sparse Polynomial Optimization Problems

Sequences of generalized Lagrangian duals and their SOS (sums of squares of polynomials) relaxations for a POP (polynomial optimization problem) are introduced. Sparsity of polynomials in the POP is used to reduce the sizes of the Lagrangian duals and their SOS relaxations. It is proved that the optimal values of the Lagrangian duals in the … Read more

Local Minima and Convergence in Low-Rank Semidefinite Programming

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

Valid inequalities based on simple mixed-integer sets

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

Sparsity in Sums of Squares of Polynomials

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

A robust SQP method for mathematical programs with linear complementarity constraints

The relationship between the mathematical program with linear complementarity constraints (MPCC) and its inequality relaxation is studied. A new sequential quadratic programming (SQP) method is presented for solving the MPCC based on this relationship. A certain SQP technique is introduced to deal with the possible infeasibility of quadratic programming subproblems. Global convergence results are derived … Read more