This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...

OBJECTIVES To determine whether alterations of endogenous asymmetric dimethylarginine (ADMA) concentration and dimethylarginine dimethylaminohydrolase (DDAH) activity are involved in endothelial dysfunction induced by glycosylated bovine serum albumin (GBSA) in rats and effects of aminoguanidine on them. METHODS Endothelium-dependent relaxation of aortic rings from Sprague-Dawley rats after t...

Gravitational search algorithm (GSA) is one of the newest swarm based optimization algorithms, which has been inspired by the Newtonian laws of gravity and motion. GSA has empirically shown to be an efficient and robust stochastic search algorithm. Since introducing GSA a convergence analysis of this algorithm has not yet been developed. This paper introduces the first attempt to a formal conve...

Gravitational search algorithm (GSA) is one of the newest swarm based optimization algorithms, which has been inspired by the Newtonian laws of gravity and motion. GSA has empirically shown to be an efficient and robust stochastic search algorithm. Since introducing GSA a convergence analysis of this algorithm has not yet been developed. This paper introduces the first attempt to a formal conve...

The minimum crossing number problem is among the oldest and most fundamental problems arising in the area of automatic graph drawing. In this paper, eight population-based meta-heuristic algorithms are utilized to tackle the minimum crossing number problem for two special types of graphs, namely complete graphs and complete bipartite graphs. A 2-page book drawing representation is employed for ...

Data clustering is an ideal way of working with a huge amount of data and looking for a structure in the dataset. In other words, clustering is the classification of the same data; the similarity among the data in a cluster is maximum and the similarity among the data in the different clusters is minimal. The innovation of this paper is a clustering method based on the Crow Search Algorithm (CS...

We present a new algorithm obtained by changing the search directions in the algorithm given in [8]. This algorithm is based on a new technique for finding the search direction and the strategy of the central path. At each iteration, we use only the full Nesterov-Todd (NT)step. Moreover, we obtain the currently best known iteration bound for the infeasible interior-point algorithms with full NT...