We present a uniied approach to the construction of belief sets for logic programs with the classical connective of negation, disjunctive logic programs, and what we call arbitrary logic programs that contain an arbitrary formula in the head and arbitrary formulas in the premises of a program rule. The approach is based on a nondetermin-istic iterative operator constrained by a dynamic preferen...

Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the pr...

bioinformatics, through the sequencing of the full genomes for many species, is increasingly relying on efficient global alignment tools exhibiting both high sensitivity and specificity. many computational algorithms have been applied for solving the sequence alignment problem. dynamic programming, statistical methods, approximation and heuristic algorithms are the most common methods applied t...

Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of pro...

The paper proposes a novel iterative control scheme based on neural networks for optimally controlling a large class of nonlinear discrete-time systems affected by an unknown time variant delay and system uncertainties. An iterative Dual Heuristic dynamic Programming (DHP) algorithm has been envisaged to design the controller which is proven to converge to the optimal one. The key elements requ...