Sharif Digital Repository

This article takes a theoretical approach to focus on the algorithmic properties of hardware/software partitioning. It proposes a method with polynomial complexity to find the global optimum of an NP-hard model partitioning problem for 75% of occurrences under some practical conditions. The global optimum is approached with a lower bound distance for the remaining 25%. Furthermore, this approach ensures finding the 2-approximate of the global optimum partition in 97% of instances where technical assumptions exist. The strategy is based on intelligently changing the parameters of the polynomial model of the partitioning problem to force it to produce (or approach) the exact solution to the... 

Recently, there has been great interest in Bio informatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solving biological problems at molecular levels. One of the classic problems of bioinformatics which has gain a lot attention lately is Haplotyping, the goal of which is categorizing SNP-fragments into two clusters and deducing a haplotype for each. Since the problem is proved to be NP-hard, several computational and heuristic methods have addressed the problem seeking feasible answers. In this work it is shown that using PCM to solve Haplotyping problem in DALY dataset yields... 

The minimum linear arrangement (MINLA) is a NP-hard problem in general. But there are some classes of graphs optimally solvable in polynomial time. In this paper, we solve the minimum linear arrangement problem for a new class of graphs (Chord graphs) in polynomial time. Also, we present a closed formula for the cost of optimal arrangement. Our motivation to solve the problem for this class of graphs is its application in optimization of peer-to-peer overlay networks. © 2008 Elsevier Inc. All rights reserved  

Maximum independent set problem is an NP-Hard one with the aim of finding the set of independent vertices with maximum possible cardinality in a graph. In this paper, we investigate a learning automaton based algorithm that finds a maximum independent set in the graph. Initially, a learning automaton is assigned to each vertex of graph. In order to find candidate independent set, a set of distributed learning automata collaborate with each other. The proposed algorithm based on learning automata is guided iteratively to the maximum independent set by updating the action probability vector. In order to study the performance of the proposed algorithm, we conducted some experiments. The... 

There is no method to determine the optimal topology for multi-layer neural networks for a given problem. Usually the designer selects a topology for the network and then trains it. Since determination of the optimal topology of neural networks belongs to class of NP-hard problems, most of the existing algorithms for determination of the topology are approximate. These algorithms could be classified into four main groups: pruning algorithms, constructive algorithms, hybrid algorithms and evolutionary algorithms. These algorithms can produce near optimal solutions. Most of these algorithms use hill-climbing method and may be stuck at local minima. In this article, we first introduce a... 

Many real-time systems are in fact isochronal, where both early and late responses are harmful to the system or lead to lower quality of service. Real-time task scheduling problems proved that are NP-hard problems. Therefore, it is necessary to apply a heuristic search strategy on these problems. In this paper, a multi-objective genetic algorithm is proposed for static task scheduling in non-overloaded isochronal soft real-time systems. Its objective is to maximize the total utility of jobs. Simulation results indicate that genetic algorithm could be a suitable heuristic search strategy for task scheduling in isochronal soft real-time systems. © 2009 IEEE  

Single Nucleotide Polymorphisms (SNPs), a single DNA base varying from one individual to another, are believed to be the most frequent form responsible for genetic differences. Genotype is the conflated information of a pair of haplotypes on homologous chromosomes. Although haplotypes have more information for disease associating than individual SNPs and genotype, it is substantially more difficult to determine haplotypes through experiments. Hence, computational methods which can reduce the cost of determining haplotypes become attractive alternatives. MEC, as a standard model for haplotype reconstruction, is fed by fragments as input to infer the best pair of haplotypes with minimum error...