Recent advances in RNA-seq technology have made identification of expressed genes affordable, and thus boosting repaid development of transcriptomic studies. Transcriptome assembly, reconstructing all expressed transc...
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Recent advances in RNA-seq technology have made identification of expressed genes affordable, and thus boosting repaid development of transcriptomic studies. Transcriptome assembly, reconstructing all expressed transcripts from RNA-seq reads, is an essential step to understand genes, proteins, and cell functions. Transcriptome assembly remains a challenging problem due to complications in splicing variants, expression levels, uneven coverage and sequencing errors. Here, we formulate the transcriptome assembly problem as path extraction on splicing graphs (or assembly graphs), and propose a novel algorithm MultiTrans for path extraction using mixed integer linear programming. MultiTrans is able to take into consideration coverage constraints on vertices and edges, the number of paths and the paired-end information simultaneously. We benchmarked MultiTrans against two state-of-the-art transcriptome assemblers, TransLiG and rnaSPAdes. Experimental results show that MultiTrans generates more accurate transcripts compared to TransLiG (using the same splicing graphs) and rnaSPAdes (using the same assembly graphs).
The computer code LPNORM implements the mathematical method of linear programming to calculate the mineralogical makeup of mineral mixtures, such as rock, sediment, or soil samples, from their bulk geochemical composi...
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The computer code LPNORM implements the mathematical method of linear programming to calculate the mineralogical makeup of mineral mixtures, such as rock, sediment, or soil samples, from their bulk geochemical composition and from the mineralogical (or geochemical) composition of the contained minerals. This method simultaneously solves the set of linear equations governing the distribution of oxides into these minerals, subject to an objective function and a set of basic constraints. LPNORM allows the user to specify what minerals will be considered for normative analysis, what their composition is (in terms of mineral formula or geochemical composition), and whether to maximizemineral abundances, minimize slack variables (oxides that can not be accounted for), or do both at once in the objective function. Independent knowledge about the abundance of one or several of the minerals in the sample can be entered as additional equality or inequality constraints. Trial-and-error approach enables the user to ''optimize'' the composition of one or a few of the contained minerals. Results of comparative tests, highlighting the efficiency, as well as the shortcomings, of LPNORM are presented.
A basic characteristic of an interior point algorithm for linear programming is the search direction. Many papers on interior point algorithms only give an implicit description of the search direction. In this report ...
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A basic characteristic of an interior point algorithm for linear programming is the search direction. Many papers on interior point algorithms only give an implicit description of the search direction. In this report we derive explicit expressions for the search directions used in many well-known algorithms. Comparing these explicit expressions gives a good insight into the similarities and differences between the various algorithms. Moreover, we give a survey of projected gradient and Newton directions for all potential and barrier functions. This is done both for the affine and projective variants.
Telecommunications service providers build highly available networks using equipment redundancy and overload protection mechanisms. However, because of network equipment misconfiguration or a natural disaster, the net...
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Telecommunications service providers build highly available networks using equipment redundancy and overload protection mechanisms. However, because of network equipment misconfiguration or a natural disaster, the network equipment failover could be unsuccessful. This article proposes a linear programming model for determining the optimal distribution of user sessions in a commercial network such that the impact of an unsuccessful network equipment failover is minimal. The model has been applied successfully during the design of a commercial network that supports approximately 5 million customers. The proposed model will be useful for managing the telecommunication networks in a way that is more robust to catastrophic failure, providing greater security and better service to users. The article also presents quantitative results that show a modest increase in end-to-end one-way speech transmission delay ranging from 3.5 to 8.1 ms. This delay is also known as mouth-to-ear delay. The article proposes improvements to the linear programming model by putting an upper limit on the potential increase in the mouth-to-ear delay.
Multi-choice programming solves some optimization problems where multiple information exists for a parameter. The aim of this paper is to select an appropriate parameter from a set of multiple choices, which optimizes...
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Multi-choice programming solves some optimization problems where multiple information exists for a parameter. The aim of this paper is to select an appropriate parameter from a set of multiple choices, which optimizes the objective function. We consider a linear programming problem where the right hand side parameters are multi-choice in nature. In this paper, the multiple choices of a parameter are considered as functional values of an affine function at some non-negative integer nodes. An interpolating polynomial is formulated using functional values at non-negative integer nodes to take care of any multi-choice parameter. After establishing interpolating polynomials of all multi-choice parameters, a mathematical programming problem is formulated. The formulated problem is treated as a nonlinear programming problem involving mixed integer type variables. It can be solved by using standard nonlinear programming software. Finally, a numerical example is presented to illustrate the solution procedure. (C) 2011 Elsevier Ltd. All rights reserved.
G allego et al. [Gallego, G., G. Iyengar, R. Phillips, A. Dubey. 2004. Managing flexible products on a network. CORC Technical Report TR-2004-01, Department of Industrial Engineering and Operations Research, Columbia ...
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G allego et al. [Gallego, G., G. Iyengar, R. Phillips, A. Dubey. 2004. Managing flexible products on a network. CORC Technical Report TR-2004-01, Department of Industrial Engineering and Operations Research, Columbia University, New York.] recently proposed a choice-based deterministic linear programming model (CDLP) for network revenue management (RM) that parallels the widely used deterministic linear programming (DLP) model. While they focused on analyzing "flexible products"-a situation in which the provider has the flexibility of using a collection of products (e. g., different flight times and/or itineraries) to serve the same market demand (e. g., an origin-destination connection)-their approach has broader implications for understanding choice-based RM on a network. In this paper, we explore the implications in detail. Specifically, we characterize optimal offer sets (sets of available network products) by extending to the network case a notion of " efficiency" developed by Talluri and van Ryzin [Talluri, K. T., G. J. van Ryzin. 2004. Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50 15-33.] for the single-leg, choice-based RM problem. We show that, asymptotically, as demand and capacity are scaled up, only these efficient sets are used in an optimal policy. This analysis suggests that efficiency is a potentially useful approach for identifying " good" offer sets on networks, as it is in the case of single-leg problems. Second, we propose a practical decomposition heuristic for converting the static CDLP solution into a dynamic control policy. The heuristic is quite similar to the familiar displacement-adjusted virtual nesting (DAVN) approximation used in traditional network RM, and it significantly improves on the performance of the static LP solution. We illustrate the heuristic on several numerical examples.
It is well known that a wide-neighborhood interior-point algorithm for linear programming performs much better in implementation than its small-neighborhood counterparts. In this paper, we provide a unified way to enl...
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It is well known that a wide-neighborhood interior-point algorithm for linear programming performs much better in implementation than its small-neighborhood counterparts. In this paper, we provide a unified way to enlarge the neighborhoods of predictor-corrector interior-point algorithms for linear programming. We prove that our methods not only enlarge the neighborhoods but also retain the so-far best known iteration complexity and superlinear (or quadratic) convergence of the original interior-point algorithms. The idea of our methods is to use the global minimizers of proximity measure functions. (C) 2006 IMACS. Published by Elsevier B.V. All rights reserved.
Nowadays, the Voice Over IP (VoIP) technology is an important component of the communications industry as well as a low-cost alternative to Public Switched Telephone Networks. Communication in VoIP networks consists o...
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Nowadays, the Voice Over IP (VoIP) technology is an important component of the communications industry as well as a low-cost alternative to Public Switched Telephone Networks. Communication in VoIP networks consists of two main phases, for example, signaling and media exchange. VoIP servers are responsible for signaling exchange using the Session Initiation Protocol (SIP) as the signaling protocol. The saturation of SIP server resources is one of the issues with the VoIP network, which causes problems such as overload or loss of energy. Resource saturation occurs mainly due to a lack of integrated server resource management. In the traditional VoIP networks, management and routing are distributed among all equipment, including servers. These servers are overloaded during peak times and face energy loss during idle times. Given the importance of this issue, this paper introduces a framework based on Software-Defined Networking technology for SIP server resource management. The advantage of this framework is to have a global view of all the server resources. In this framework, the resource allocation optimization problem and resource autoscaling are presented to deal with the problems posed. The goal is to maximize total throughput and minimize energy consumption. In this regard, we seek to strike a balance between efficiency and energy. The proposed framework is implemented in the actual testbed. The results show that the proposed framework has succeeded in achieving these goals.
Two linear programming data reconciliation approaches based on the independent flows technique for multicomponent processes are presented. The first method which uses the relationships between independent flows and in...
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It has been shown [8] that numerous interior-point algorithms for linear programming (LP) generate solution sequences that converge to strict complementarity solutions, or interior solutions on the optimal face. In th...
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It has been shown [8] that numerous interior-point algorithms for linear programming (LP) generate solution sequences that converge to strict complementarity solutions, or interior solutions on the optimal face. In this note we further establish a theoretical base for Gay's test (Gay, 1989) to identify the optimal face, and develop a new termination procedure to obtain an exact solution on the optimal face. We also report some numerical results for solving a set of LP test problems, each of which has a highly degenerate and unbounded optimal face.
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