in this paper we introduced a new priority rule algorithm in human queues. the suggested method is applicable in human lines with different demands (serving times) for different customers. in this method, the waiting time for each customer is related to the volume of demand. a common example of such a system is a bakery line. the usual priority rule algorithm in this kind of queue is first-in-f...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

An upward drawing of a rooted tree T is a planar straight-line drawing of T where the vertices of T are placed on a set of horizontal lines, called layers, such that for each vertex u of T , no child of u is placed on a layer vertically above the layer on which u has been placed. In this paper we give a linear-time algorithm to obtain an upward drawing of a given rooted tree T on the minimum nu...

the markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. on the other hand, most managers prefer to manage a small portfolio of available assets in place of a huge portfolio. it can be analogized to cardinal constrains, that is, constrains related to minimum and maximum curr...

Network environments always can be invaded by intruder agents. In networks where nodes are performing some computations, intruder agents might contaminate some nodes. Therefore, problem of decontaminating a network infected by intruder agents is one of the major problems in these networks. In this paper, we present a distributed asynchronous local algorithm for decontaminating a network. In mos...

In this paper the accuracy of two machine learning algorithms including SVM and Bayesian Network are investigated as two important algorithms in diagnosis of Parkinson’s disease. We use Parkinson's disease data in the University of California, Irvine (UCI). In order to optimize the SVM algorithm, different kernel functions and C parameters have been used and our results show that SVM with C par...

A novel hybrid method for tracking multiple indistinguishable maneuvering targets using a wireless sensor network is introduced in this paper. The problem of tracking the location of targets is formulated as a Maximum Likelihood Estimation. We propose a hybrid optimization method, which consists of an iterative and a heuristic search method, for finding the location of targets simultaneously. T...

Grouping datasets plays an important role in many scientific researches. Depending on data features and applications, different constrains are imposed on groups, while having groups with similar members is always a main criterion. In this paper, we propose an algorithm for grouping the objects with random labels, nominal features having too many nominal attributes. In addition, the size constra...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...