Schwach verkoppelte Ungleichungssysteme und konvexe Spline-Interpolation.
Schwankungsbereiche linearer Optimierungsaufgaben.
Semi-infinite programming problems
Sensor Location Problem for a Multigraph
MSC 2010: 05C50, 15A03, 15A06, 65K05, 90C08, 90C35We introduce sparse linear underdetermined systems with embedded network structure. Their structure is inherited from the non-homogeneous network ow programming problems with nodes of variable intensities. One of the new applications of the researched underdetermined systems is the sensor location problem (SLP) for a multigraph. That is the location of the minimum number of sensors in the nodes of the multigraph, in order to determine the arcs ow...
Simulated annealing algorithm for the minimum weighted perfect euclidean matching problem
Smoothing functions and algorithm for nonsymmetric circular cone complementarity problems
There has been much interest in studying symmetric cone complementarity problems. In this paper, we study the circular cone complementarity problem (denoted by CCCP) which is a type of nonsymmetric cone complementarity problem. We first construct two smoothing functions for the CCCP and show that they are all coercive and strong semismooth. Then we propose a smoothing algorithm to solve the CCCP. The proposed algorithm generates an infinite sequence such that the value of the merit function converges...
Smoothing Noisy Data with Spline Functions. Estimating the Correct Degree of Smoothing by the Method of Generalized Cross-Validation.
Solution of projection problems over polytopes.
Solving convex program via Lagrangian decomposition
We consider general convex large-scale optimization problems in finite dimensions. Under usual assumptions concerning the structure of the constraint functions, the considered problems are suitable for decomposition approaches. Lagrangian-dual problems are formulated and solved by applying a well-known cutting-plane method of level-type. The proposed method is capable to handle infinite function values. Therefore it is no longer necessary to demand the feasible set with respect to the non-dualized...
Solving the Task Assignment Problem with a Variable Neighborhood Search
In this paper a variable neighborhood search (VNS) approach for the task assignment problem (TAP) is considered. An appropriate neighborhood scheme along with a shaking operator and local search procedure are constructed specifically for this problem. The computational results are presented for the instances from the literature, and compared to optimal solutions obtained by the CPLEX solver and heuristic solutions generated by the genetic algorithm. It can be seen that the proposed VNS approach reaches...
Some notes on the quasi-Newton methods
A survey note whose aim is to establish the heuristics and natural relations in a class of Quasi-Newton methods in optimization problems. It is shown that a particular algorithm of the class is specified by characcterizing some parameters (scalars and matrices) in a general solution of a matrix equation.
Some optimization problems on solubility sets of separable Max-Min equations and inequalities
Sparse Null Basis Computations in Structural Optimization.
Stability of lagrangian duality for nonconvex quadratic programming. Solution methods and applications in computer vision
Staging in Balas' algorithm
Strategies for LP-based solving a general class of scheduling problems.
In this work we describe some strategies that have been proved to be very efficient for solving the following type of scheduling problems: Assume a set of jobs is to be performed along a planning horizon by selecting one from several alternatives for doing so. Besides selecting the alternative for each job, the target consists of choosing the periods at which each component of the work will be done, such that a set of scheduling and technological constraints is satisfied. The problem is formulated...
Strong convergence of a new iterative method for infinite family of generalized equilibrium and fixed-point problems of nonexpansive mappings in Hilbert spaces.
Strong Uniqueness and Second Order Convergence in Nonlinear Discrete Approximation.
Subgradient optimization and large scale programming : an application to optimum multicommodity network synthesis with security constraints
Sufficient decrease principle on Riemannian manifolds.