En
  • دکتری (1395)

    مهندسی کامپیوتر - مهندسی نرم‌افزار

    صنعتی امیرکبیر، تهران، ایران

  • کارشناسی‌ارشد (1389)

    مهندسی کامپیوتر - مهندسی نرم‌افزار

    صنعتی امیرکبیر، تهران، ایران

  • کارشناسی (1389)

    مهندسی فناوری اطلاعات

    صنعتی امیرکبیر، تهران، ایران

  • کارشناسی (1387)

    مهندسی کامپیوتر - مهندسی نرم‌افزار

    صنعتی امیرکبیر، تهران، ایران

  • هوش مصنوعی (یادگیری تقویتی)
  • علوم داده و کلان‌داده
  • علوم شبکه (تحلیل شبکه‌های اجتماعی)
  • الگوریتم

    مهدی رعایائی مدارک کارشناسی، کارشناسی ارشد و دکتری خود را به ترتیب در سال‌های 87، 89 و 95 در رشته مهندسی کامپیوتر از دانشگاه صنعتی امیرکبیر (پلی‌تکنیک تهران) اخذ کرده است. همچنین او در سال 89 کارشناسی دوم خود را در رشته فناوری اطلاعات از دانشگاه امیرکبیر اخذ نمود. او در حال حاضر، استادیار گروه مهندسی کامپیوتر دانشکده برق و کامپیوتر دانشگاه تربیت مدرس تهران می‌باشد.

    ارتباط

    رزومه

    On the binarization of Grey Wolf optimizer: a novel binary optimizer algorithm

    M Roayaei
    Journal Papers , , {Pages }

    Abstract

    On the parameterized complexity of the problem of inferring protein–protein interaction directions based on cause–effect pairs

    Mehdy Roayaei
    Journal PapersNetwork Modeling Analysis in Health Informatics and Bioinformatics , Volume 8 , Issue 1, 2019 December 1, {Pages 11 }

    Abstract

    We consider the following problem: given an undirected (mixed) network and a set of ordered source–target pairs, or cause–effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source–target path. This is called the maximum graph orientation problem, and has applications in understanding interactions in protein–protein interaction networks. Since this problem is NP-hard, we take the parameterized complexity viewpoint and study the parameterized (in) tractability of the problem with respect to various parameters on both undirected and mixed networks. In the undirected case, we determine the parameterized complexity of the problem (for non-fixed and fixed paths) with respect to the number of satisfi

    Minimum Cardinality Point-to-point Connectivity Augmentation Problem

    Mehdy Roayaei, MohammadReza Razzazi
    Journal PapersFundamenta Informaticae , Volume 160 , Issue 4, 2018 January 1, {Pages 447-463 }

    Abstract

    We consider an augmentation problem to establish point-to-point connectivity on unweighted graphs where there is no restriction on choosing the augmenting edges (arcs). Given a directed (an undirected) graph G and set P={(s i, t i): 1≤ i≤ m} of pairs of vertices in the graph, one has to find the minimum cardinality set of arcs (edges) to be added to the graph so that the resulting graph has (can be oriented in order to have) directed paths between the specified pairs of vertices. In the case of undirected graphs, an efficient polynomial-time algorithm is presented. In the case of directed graphs, we find that this problem is NP-hard. In addition, we show that it is fixed-parameter tractable with respect to the combined parameter the num

    Parameterized Complexity of Directed Steiner Network with Respect to Shared Vertices and Arcs

    Mehdy Roayaei, MohammadReza Razzazi
    Journal PapersInternational Journal of Foundations of Computer Science , Volume 29 , Issue 07, 2018 November , {Pages 1215-1230 }

    Abstract

    We consider the directed Steiner network problem, where given a weighted directed graph and pairs of vertices , one has to find the minimum weight subgraph of that contains path from to for all . We search for the main cause of the complexity of the problem and introduce the notions of junction vertex and shared segment in an optimal solution. We study the parameterized complexity of the problem with respect to these parameters and achieve several parameterized hardness results. Also, we present two output-sensitive algorithms for the problem, which are much simpler and easier to implement than the previously best known one; and in addition, when the paths corresponding to the input pairs have few shared vertices or arcs in the optima

    Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks

    Mehdy Roayaei, MohammadReza Razzazi
    Journal PapersarXiv preprint arXiv:1706.00911 , 2017 June 3, {Pages }

    Abstract

    We consider the following problem: Given an undirected (mixed) network and a set of ordered source-target, or cause-effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source-target path. This is called maximum graph orientation problem, and has applications in understanding interactions in protein-protein interaction networks and protein-DNA interaction networks. We have studied the problem on both undirected and mixed networks. In the undirected case, we determine the parameterized complexity of the problem (for non-fixed and fixed paths) with respect to the number of satisfied pairs, which has been an open problem. Also, we present an exact algorithm which outperforms the previous algorithms on tree

    Augmenting weighted graphs to establish directed point-to-point connectivity

    Mehdy Roayaei, Mohammadreza Razzazi
    Journal PapersJournal of Combinatorial Optimization , Volume 33 , Issue 3, 2017 April 1, {Pages 1030-1056 }

    Abstract

    We consider an augmentation problem on undirected and directed graphs, where given a directed (an undirected) graph G and p pairs of vertices , one has to find the minimum weight set of arcs (edges) to be added to the graph so that the resulting graph has (can be oriented to have) directed paths between the specified pairs of vertices. In the undirected case, we present an FPT-algorithm with respect to the number of new edges. Also, we have implemented and evaluated the algorithm on some real-world networks to show its efficiency in decreasing the size of input graphs and converting them to much smaller kernels. In the directed case, we consider the complexity of the problem with respect to the various parameters and present

    An FPT-algorithm for modifying a graph of bounded treewidth to decrease the size of its dominating set using minimum modification

    Mehdy Roayaei, Mohammadreza Razzazi
    Journal PapersInformation Processing Letters , Volume 116 , Issue 9, 2016 September 1, {Pages 590-594 }

    Abstract

    In this paper, we study the problem of modifying a graph such that the resulting graph has a dominating set of size at most k. Solving this problem determines the minimum number of edges to be added to a given graph such that at most k vertices can dominate all vertices. We show that this problem is NP-hard, and therefore, has no polynomial-time algorithm (unless P= NP). Also, we show that the problem is FPT parameterized by the treewidth of the input graph. Furthermore, we show that the problem parameterized by k is W [2]-hard and belongs to W [P].

    Using sticker model of DNA computing to solve domatic partition, kernel and induced path problems

    Mohammadreza Razzazi, Mehdy Roayaei
    Journal PapersInformation Sciences , Volume 181 , Issue 17, 2011 September 1, {Pages 3581-3600 }

    Abstract

    DNA computing as a powerful interdisciplinary field has been found to be very useful and applicable for solving NP-complete and intractable problems because of its huge power in parallel processing. In recent years many efforts have been done to solve NP-complete and time consuming problems with the help of DNA computing. In this paper, we use sticker model (one of the most well-known models of DNA computing) to present three DNA algorithms for solving three different NP-complete graph-based problems for the first time: domatic partition, kernel and induced path. Also we have simulated these algorithms to show their correctness.

    Improving Fairness of Influence Maximization in Social Networks Using Grey Wolf Optimizer

    Behnam Razzaghi, Mehdy Roayaei Ardakany
    Journal Papers , January , {Pages }

    Abstract

    Influence Maximization is one of the most popular problems in social networks, which has many applications in real-world networks. Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. However, fairness has not been considered widely in this domain. An important question is whether the benefits of such information propagation in a social network is fairly distributed across different groups in the population. Thus, single-objective influence maximization problem turns to the multi-objective problem, in which both the spread of influence and fairness must be considered. In this paper, we first introduce the measure we use for measuring fairness i

    دروس نیمسال جاری

    • كارشناسي ارشد
      پايگاه داده پيشرفته ( واحد)
      دانشکده مهندسی برق و کامپیوتر، گروه مهندسي كامپيوتر
    • كارشناسي ارشد
      هوش مصنوعي پيشرفته ( واحد)

    دروس نیمسال قبل

    • كارشناسي ارشد
      الگوريتم هاي پيشرفته ( واحد)
      دانشکده مهندسی برق و کامپیوتر، گروه مهندسي كامپيوتر
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      افروغه, علي
      بيشينه‌سازي امتياز در بازي‌هاي تصادفي match-3 با استفاده از يادگيري تقويتي
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