Dynamic games are an effective paradigm for dealing with the control of multiple interacting actors. This paper introduces augmented Lagrangian GAME-theoretic solver (ALGAMES), a that handles trajectory-optimization problems actors and general nonlinear state input constraints. Its novelty resides in satisfying first-order optimality conditions quasi-Newton root-finding algorithm rigorously enf...

1. Abstract This paper describes the development of an augmented Lagrangian optimization method for the numerical simulation of the inflation process in the design of inflated space structures. Although the Newton-Raphson scheme has proved to be efficient for solving many non linear problems, it can lead to lacks of convergence when it is applied to the simulation of the inflation process. As a...

This paper presents an augmented Lagrangian methodology with a stochastic population based algorithm for solving nonlinear constrained global optimization problems. The method approximately solves a sequence of simple bound global optimization subproblems using a fish swarm intelligent algorithm. A stochastic convergence analysis of the fish swarm iterative process is included. Numerical result...

A new recursive augmented Lagrangian (AL) algorithm is presented for reconstruction of a 3D wave field for intensity-only measurements obtained from two or more sensor planes parallel to the object plane. This reconstruction is framed as a maximum likelihood constrained nonlinear optimization problem for Gaussian additive noise observations. A contribution of this paper concerns a development o...

HB and HB are two shared-key, unidirectional authentication protocols whose extremely low computational cost makes them potentially well-suited for severely resource-constrained devices. Security of these protocols is based on the conjectured hardness of learning parity with noise; that is, learning a secret s given “noisy” dot products of s that are incorrect with probability ε. Although the p...

Numerical identification of diffusion parameters in a nonlinear convection–diffusion equation is studied. This partial differential equation arises as the saturation equation in the fractional flow formulation of the two–phase porous media flow equations. The forward problem is discretized with the finite difference method, and the identification problem is formulated as a constrained minimizat...

Abstract. The aim of this paper is to investigate the application of a semiimplicit additive operator splitting scheme based binary level set method to source reconstruction problems. We reformulate the original model to be a new constrained optimization problem under the binary level set framework and solve it by the augmented Lagrangian method. Then we propose an efficient gradient-type algor...

Motion planning for manipulators under task space constraints is difficult as it constrains the joint configurations to always lie on an implicitly defined manifold. It is possible to view task constrained motion planning as an optimization problem with non-linear equality constraints which can be solved by general non-linear optimization techniques. In this paper, we present a novel custom opt...

Hybridization of genetic algorithms with local search approaches can enhance their performance in global optimization. Genetic algorithms, as most population based algorithms, require a considerable number of function evaluations. This may be an important drawback when the functions involved in the problem are computationally expensive as it occurs in most real world problems. Thus, in order to...

As a first-order method, the augmented Lagrangian method (ALM) is a benchmark solver for linearly constrained convex programming, and in practice some semi-definite proximal terms are often added to its primal variable's subproblem to make it more implementable. In this paper, we propose an accelerated PALM with indefinite proximal regularization (PALM-IPR) for convex programming with linear co...