A Single Period Inventory Model of a Deteriorating Item Sold from Two Shops With Shortage Via Genetic Algorithm
A Six States Minimal Time Solution to the Firing Squad Synchronization Problem
A Slideing Mesh-Mortar Method for a two Dimensional Currents Model of Electric Engines
The paper deals with the application of a non-conforming domain decomposition method to the problem of the computation of induced currents in electric engines with moving conductors. The eddy currents model is considered as a quasi-static approximation of Maxwell equations and we study its two-dimensional formulation with either the modified magnetic vector potential or the magnetic field as primary variable. Two discretizations are proposed, the first one based on curved finite elements and the...
A sliding Mesh-Mortar method for a two dimensional Eddy currents model of electric engines
The paper deals with the application of a non-conforming domain decomposition method to the problem of the computation of induced currents in electric engines with moving conductors. The eddy currents model is considered as a quasi-static approximation of Maxwell equations and we study its two-dimensional formulation with either the modified magnetic vector potential or the magnetic field as primary variable. Two discretizations are proposed, the first one based on curved finite elements and the...
A Software for the Visualisationof Differential Geometry
A software reliability growth model with two types of errors
A solvable case of the set-partitioning problem
A space lower bound for acceptance by one-way -alternating machines
A Space Lower Bound for Acceptance by One-Way Π2-Alternating Machines
We show that one-way Π2-alternating Turing machines cannot accept unary nonregular languages in o(log n) space. This holds for an accept mode of space complexity measure, defined as the worst cost of any accepting computation. This lower bound should be compared with the corresponding bound for one-way Σ2-alternating machines, that are able to accept unary nonregular languages in space O(log log n). Thus, Σ2-alternation is more powerful than Π2-alternation for space bounded one-way machines with...
A sparse dynamic programming algorithm for alignment with non-overlapping inversions
Alignment of sequences is widely used for biological sequence comparisons, and only biological events like mutations, insertions and deletions are considered. Other biological events like inversions are not automatically detected by the usual alignment algorithms, thus some alternative approaches have been tried in order to include inversions or other kinds of rearrangements. Despite many important results in the last decade, the complexity of the problem of alignment with inversions is still unknown....
A sparse dynamic programming algorithm for alignment with non-overlapping inversions
Alignment of sequences is widely used for biological sequence comparisons, and only biological events like mutations, insertions and deletions are considered. Other biological events like inversions are not automatically detected by the usual alignment algorithms, thus some alternative approaches have been tried in order to include inversions or other kinds of rearrangements. Despite many important results in the last decade, the complexity of the problem of alignment with inversions is...
A special form of grammars
A split&push approach to orthogonal drawing.
A static sorting algorithm for sytems with mobile catalysts.
A stochastic approach to robot plan formation
A stochastic mirror-descent algorithm for solving over an multi-agent system
In this paper, we consider a distributed stochastic computation of with local set constraints over an multi-agent system, where each agent over the network only knows a few rows or columns of matrixes. Through formulating an equivalent distributed optimization problem for seeking least-squares solutions of , we propose a distributed stochastic mirror-descent algorithm for solving the equivalent distributed problem. Then, we provide the sublinear convergence of the proposed algorithm. Moreover,...
A strategy learning model for autonomous agents based on classification
In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation...
A streaming approach for sparse matrix products and its application in Galerkin multigrid methods.
A survey of certain digitization projects in Serbia
A survey of factors influencing MLP error surface