On parameters of an evaluation function for heuristic search as a path problem
On polyhedral games
On precision of stochastic optimization based on estimates from censored data
In the framework of a stochastic optimization problem, it is assumed that the stochastic characteristics of optimized system are estimated from randomly right-censored data. Such a case is frequently encountered in time-to-event or lifetime studies. The analysis of precision of such a solution is based on corresponding theoretical properties of estimated stochastic characteristics. The main concern is to show consistency of optimal solution even in the random censoring case. Behavior of solutions...
On primal-dual stability in convex optimization.
On properties of solutions for two functional equations arising in dynamic programming.
On quasi-solution to infeasible linear complementarity problem obtained by Lemke’s method
For a linear complementarity problem with inconsistent system of constraints a notion of quasi-solution of Tschebyshev type is introduced. It’s shown that this solution can be obtained automatically by Lemke’s method if the constraint matrix of the original problem is copositive plus or belongs to the intersection of matrix classes P 0 and Q 0.
On robustness of set-valued maps and marginal value functions
The ideas of robust sets, robust functions and robustness of general set-valued maps were introduced by Chew and Zheng [7,26], and further developed by Shi, Zheng, Zhuang [18,19,20], Phú, Hoffmann and Hichert [8,9,10,17] to weaken up the semi-continuity requirements of certain global optimization algorithms. The robust analysis, along with the measure theory, has well served as the basis for the integral global optimization method (IGOM) (Chew and Zheng [7]). Hence, we have attempted to extend the...
On robustness of the regularity property of maps
On Rohn's relative sensitivity coefficient of the optimal value for a linear-fractional program
In this note we consider a linear-fractional programming problem with equality linear constraints. Following Rohn, we define a generalized relative sensitivity coefficient measuring the sensitivity of the optimal value for a linear program and a linear-fractional minimization problem with respect to the perturbations in the problem data. By using an extension of Rohn's result for the linear programming case, we obtain, via Charnes-Cooper variable change, the relative sensitivity coefficient for...
On second–order Taylor expansion of critical values
Studying a critical value function in parametric nonlinear programming, we recall conditions guaranteeing that is a function and derive second order Taylor expansion formulas including second-order terms in the form of certain generalized derivatives of . Several specializations and applications are discussed. These results are understood as supplements to the well–developed theory of first- and second-order directional differentiability of the optimal value function in parametric optimization....
On self-optimizing control of Markov processes
On semidefinite bounds for maximization of a non-convex quadratic objective over the l1 unit ball
We consider the non-convex quadratic maximization problem subject to the l1 unit ball constraint. The nature of the l1 norm structure makes this problem extremely hard to analyze, and as a consequence, the same difficulties are encountered when trying to build suitable approximations for this problem by some tractable convex counterpart formulations. We explore some properties of this problem, derive SDP-like relaxations and raise open questions.
On Shapley KKMS theorem
On smoothing of parametric minimax-functions and generalized max-functions via regularization.
On Solving the Maximum Betweenness Problem Using Genetic Algorithms
In this paper a genetic algorithm (GA) is applied on Maximum Betweennes Problem (MBP). The maximum of the objective function is obtained by finding a permutation which satisfies a maximal number of betweenness constraints. Every permutation considered is genetically coded with an integer representation. Standard operators are used in the GA. Instances in the experimental results are randomly generated. For smaller dimensions, optimal solutions of MBP are obtained by total enumeration. For those...
On some Aspects of the Matrix Data Perturbation in Linear Program
On some Interconnections Between Combinatorial Optimization and Extremal Graph Theory
On some limit properties of the reward from a Markov replacement process
On some polynomial solvable cases of the generalized minimum spanning tree problem.
On some properties of paramonotone operators.