A generalized Markov decision process
A generalized proximal point algorithm for the nonlinear complementarity problem
A generalized proximal point algorithm for the nonlinear complementarity problem
We consider a generalized proximal point method (GPPA) for solving the nonlinear complementarity problem with monotone operators in Rn. It differs from the classical proximal point method discussed by Rockafellar for the problem of finding zeroes of monotone operators in the use of generalized distances, called φ-divergences, instead of the Euclidean one. These distances play not only a regularization role but also a penalization one, forcing the sequence generated by the method to remain in the...
A generalized solution of a nonconvex minimization problem and its stability
A Generalized Upper Bounded Technique for a Linear Fractional Program.
A generalized varying-domain optimization method for fuzzy goal programming with priorities based on a genetic algorithm
A generic result in vector optimization.
A Genetic Algorithm Approach to the Buyers' Welfare Problem of Product Line Design: A Comparative Computational Study
A Genetic Algorithm for Composing Music
A genetic algorithm for solving multiple warehouse layout problem
A genetic based approach to the type I structure identification problem.
A geometric point of view on mean-variance models
This paper deals with the mathematics of the Markowitz theory of portfolio management. Let E and V be two homogeneous functions defined on ℝⁿ, the first linear, the other positive definite quadratic. Furthermore let Δ be a simplex contained in ℝⁿ (the set of admissible portfolios), for example Δ : x₁+ ... + xₙ = 1, . Our goal is to investigate the properties of the restricted mappings (V,E):Δ → ℝ² (the so called Markowitz mappings) and to classify them. We introduce the notion of a generic model...
A geometrical method in combinatorial complexity
A lower bound for the number of comparisons is obtained, required by a computational problem of classification of an arbitrarily chosen point of the Euclidean space with respect to a given finite family of polyhedral (non-convex, in general) sets, covering the space. This lower bound depends, roughly speaking, on the minimum number of convex parts, into which one can decompose these polyhedral sets. The lower bound is then applied to the knapsack problem.
A global method for some class of optimization and control problems.
A Global Stochastic Optimization Method for Large Scale Problems
In this paper, a new hybrid simulated annealing algorithm for constrained global optimization is proposed. We have developed a stochastic algorithm called ASAPSPSA that uses Adaptive Simulated Annealing algorithm (ASA). ASA is a series of modifications to the basic simulated annealing algorithm (SA) that gives the region containing the global solution of an objective function. In addition, Simultaneous Perturbation Stochastic Approximation (SPSA)...
A Globalization Scheme for the Generalized Gauss-Newton Method.
A globally convergent neurodynamics optimization model for mathematical programming with equilibrium constraints
This paper introduces a neurodynamics optimization model to compute the solution of mathematical programming with equilibrium constraints (MPEC). A smoothing method based on NPC-function is used to obtain a relaxed optimization problem. The optimal solution of the global optimization problem is estimated using a new neurodynamic system, which, in finite time, is convergent with its equilibrium point. Compared to existing models, the proposed model has a simple structure, with low complexity. The...
A globally convergent non-interior point algorithm with full Newton step for second-order cone programming
A non-interior point algorithm based on projection for second-order cone programming problems is proposed and analyzed. The main idea of the algorithm is that we cast the complementary equation in the primal-dual optimality conditions as a projection equation. By using this reformulation, we only need to solve a system of linear equations with the same coefficient matrix and compute two simple projections at each iteration, without performing any line search. This algorithm can start from an arbitrary...
A goal programming model for selecting a facility location site
A good approximation of the inventory level in a perishable inventory system