This paper proposes a predictor-corrector primal-dual interior point method which introduces line search procedures IPLS in both the predictor and corrector steps. The Fibonacci search technique is used in the predictor step, while an Armijo line search is used in the corrector step. The method is developed for application to the economic dispatch ED problem studied in the field of power system...

Bundle methods have been used frequently to solve nonsmooth optimization problems. In these methods, subgradient directions from past iterations are accumulated in a bundle, and a trial direction is obtained by performing quadratic programming based on the information contained in the bundle. A line search is then performed along the trial direction, generating a serious step if the function va...

This paper introduces the variable objective search framework for combinatorial optimization. The method utilizes different objective functions used in alternative mathematical programming formulations of the same combinatorial optimization problem in an attempt to improve the solutions obtained using each of these formulations individually. The proposed technique is illustrated using alternati...

1 Introduction We introduce a new approach for similarity search in 3-D protein databases. By using histograms, we define adaptable similarity models that address the 3-D shape as well as chemical properties of proteins. Quadratic forms are employed as similarity distance functions for which efficient query processing algorithms are available [Sei 97]. Experimental examples illustrate the appli...

In this paper, we report an application of the life span method (LSM), a variant of tabu search introduced by the authors, to the quadratic assignment problem which has applications on facility location and backboard wiring, etc. We discuss how to adapt the LSM to the quadratic assignment problem and compare the performance with previous heuristics. The main purpose of this paper is to perform ...

Stochastic robustness synthesis is used to find compensators that solve a benchmark problem. The synthesis minimizes a robustness cost function that is the weighted quadratic sum of stochastic robustness metrics. These metrics probability of instability, probability of actuator saturation, and probability of settling time violation are estimated using Monte Carlo analysis. A simple search metho...

Multi-start algorithms are a common and effective tool for metaheuristic searches. In this paper we amplify multi-start capabilities by employing the parallel processing power of the graphics processer unit (GPU) to quickly generate a diverse starting set of solutions for the Unconstrained Binary Quadratic Optimization Problem which are evaluated and used to implement screening methods to selec...

An extension of the Gauss{Newton method for nonlinear equations to convex composite optimization is described and analyzed. Local quadratic convergence is established for the minimization of h F under two conditions, namely h has a set of weak sharp minima, C, and there is a regular point of the inclusion F(x) 2 C. This result extends a similar convergence result due to Womersley which employs ...

A readily implementable algorithm is given for minimizing any convex, not necessarily differentiable, function/of several variables. At each iteration the method requires only one approximate evaluation of /and its E-subgradient, and finds a search direction by solving a small quadratic programming problem. The algorithm generates a minimizing sequence of points, which converges to a solution w...