Next Issue
Volume 9, June
Previous Issue
Volume 9, December

Table of Contents

Algorithms, Volume 9, Issue 1 (March 2016)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Select all
Export citation of selected articles as:
Open AccessArticle
Multivariate Algorithmics for Finding Cohesive Subnetworks
Algorithms 2016, 9(1), 21; https://doi.org/10.3390/a9010021 - 16 Mar 2016
Cited by 16 | Viewed by 1890
Abstract
Community detection is an important task in the analysis of biological, social or technical networks. We survey different models of cohesive graphs, commonly referred to as clique relaxations, that are used in the detection of network communities. For each clique relaxation, we [...] Read more.
Community detection is an important task in the analysis of biological, social or technical networks. We survey different models of cohesive graphs, commonly referred to as clique relaxations, that are used in the detection of network communities. For each clique relaxation, we give an overview of basic model properties and of the complexity of the problem of finding large cohesive subgraphs under this model. Since this problem is usually NP-hard, we focus on combinatorial fixed-parameter algorithms exploiting typical structural properties of input networks. Full article
Show Figures

Figure 1

Open AccessArticle
The Iterative Solution to Discrete-Time H Control Problems for Periodic Systems
Algorithms 2016, 9(1), 20; https://doi.org/10.3390/a9010020 - 14 Mar 2016
Cited by 1 | Viewed by 1487
Abstract
This paper addresses the problem of solving discrete-time H ∞ control problems for periodic systems. The approach for solving such a type of equations is well known in the literature. However, the focus of our research is set on the numerical computation of [...] Read more.
This paper addresses the problem of solving discrete-time H ∞ control problems for periodic systems. The approach for solving such a type of equations is well known in the literature. However, the focus of our research is set on the numerical computation of the stabilizing solution. In particular, two effective methods for practical realization of the known iterative processes are described. Furthermore, a new iterative approach is investigated and applied. On the basis of numerical experiments, we compare the presented methods. A major conclusion is that the new iterative approach is faster than rest of the methods and it uses less RAM memory than other methods. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Open AccessReview
Review of Recent Advances in the Application of the Wavelet Transform to Diagnose Cracked Rotors
Algorithms 2016, 9(1), 19; https://doi.org/10.3390/a9010019 - 14 Mar 2016
Cited by 17 | Viewed by 1652
Abstract
Wavelet transform (WT) has been used in the diagnosis of cracked rotors since the 1990s. At present, WT is one of the most commonly used tools to treat signals in several fields. Understandably, this has been an area of extensive scientific research, which [...] Read more.
Wavelet transform (WT) has been used in the diagnosis of cracked rotors since the 1990s. At present, WT is one of the most commonly used tools to treat signals in several fields. Understandably, this has been an area of extensive scientific research, which is why this paper aims to summarize briefly the major advances in the field since 2008. The present review considers advances in the use and application of WT, the selection of the parameters used, and the key achievements in using WT for crack diagnosis. Full article
Show Figures

Figure 1

Open AccessArticle
Constructing Frozen Jacobian Iterative Methods for Solving Systems of Nonlinear Equations, Associated with ODEs and PDEs Using the Homotopy Method
Algorithms 2016, 9(1), 18; https://doi.org/10.3390/a9010018 - 11 Mar 2016
Cited by 5 | Viewed by 1943
Abstract
A homotopy method is presented for the construction of frozen Jacobian iterative methods. The frozen Jacobian iterative methods are attractive because the inversion of the Jacobian is performed in terms of LUfactorization only once, for a single instance of the iterative method. We [...] Read more.
A homotopy method is presented for the construction of frozen Jacobian iterative methods. The frozen Jacobian iterative methods are attractive because the inversion of the Jacobian is performed in terms of LUfactorization only once, for a single instance of the iterative method. We embedded parameters in the iterative methods with the help of the homotopy method: the values of the parameters are determined in such a way that a better convergence rate is achieved. The proposed homotopy technique is general and has the ability to construct different families of iterative methods, for solving weakly nonlinear systems of equations. Further iterative methods are also proposed for solving general systems of nonlinear equations. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Open AccessArticle
Co-Clustering under the Maximum Norm
Algorithms 2016, 9(1), 17; https://doi.org/10.3390/a9010017 - 25 Feb 2016
Viewed by 2293
Abstract
Co-clustering, that is partitioning a numerical matrix into “homogeneous” submatrices, has many applications ranging from bioinformatics to election analysis. Many interesting variants of co-clustering are NP-hard. We focus on the basic variant of co-clustering where the homogeneity of a submatrix is defined in [...] Read more.
Co-clustering, that is partitioning a numerical matrix into “homogeneous” submatrices, has many applications ranging from bioinformatics to election analysis. Many interesting variants of co-clustering are NP-hard. We focus on the basic variant of co-clustering where the homogeneity of a submatrix is defined in terms of minimizing the maximum distance between two entries. In this context, we spot several NP-hard, as well as a number of relevant polynomial-time solvable special cases, thus charting the border of tractability for this challenging data clustering problem. For instance, we provide polynomial-time solvability when having to partition the rows and columns into two subsets each (meaning that one obtains four submatrices). When partitioning rows and columns into three subsets each, however, we encounter NP-hardness, even for input matrices containing only values from {0, 1, 2}. Full article
Show Figures

Figure 1

Open AccessArticle
Multiband and Lossless Compression of Hyperspectral Images
Algorithms 2016, 9(1), 16; https://doi.org/10.3390/a9010016 - 18 Feb 2016
Cited by 6 | Viewed by 1695
Abstract
Hyperspectral images are widely used in several real-life applications. In this paper, we investigate on the compression of hyperspectral images by considering different aspects, including the optimization of the computational complexity in order to allow implementations on limited hardware (i.e., hyperspectral [...] Read more.
Hyperspectral images are widely used in several real-life applications. In this paper, we investigate on the compression of hyperspectral images by considering different aspects, including the optimization of the computational complexity in order to allow implementations on limited hardware (i.e., hyperspectral sensors, etc.). We present an approach that relies on a three-dimensional predictive structure. Our predictive structure, 3D-MBLP, uses one or more previous bands as references to exploit the redundancies among the third dimension. The achieved results are comparable, and often better, with respect to the other state-of-art lossless compression techniques for hyperspectral images. Full article
Show Figures

Figure 1

Open AccessArticle
A Geometric Orthogonal Projection Strategy for Computing the Minimum Distance Between a Point and a Spatial Parametric Curve
Algorithms 2016, 9(1), 15; https://doi.org/10.3390/a9010015 - 06 Feb 2016
Cited by 2 | Viewed by 2450
Abstract
A new orthogonal projection method for computing the minimum distance between a point and a spatial parametric curve is presented. It consists of a geometric iteration which converges faster than the existing Newton’s method, and it is insensitive to the choice of initial [...] Read more.
A new orthogonal projection method for computing the minimum distance between a point and a spatial parametric curve is presented. It consists of a geometric iteration which converges faster than the existing Newton’s method, and it is insensitive to the choice of initial values. We prove that projecting a point onto a spatial parametric curve under the method is globally second-order convergence. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Show Figures

Figure 1

Open AccessArticle
Two Efficient Derivative-Free Iterative Methods for Solving Nonlinear Systems
Algorithms 2016, 9(1), 14; https://doi.org/10.3390/a9010014 - 01 Feb 2016
Cited by 3 | Viewed by 1810
Abstract
In this work, two multi-step derivative-free iterative methods are presented for solving system of nonlinear equations. The new methods have high computational efficiency and low computational cost. The order of convergence of the new methods is proved by a development of an inverse [...] Read more.
In this work, two multi-step derivative-free iterative methods are presented for solving system of nonlinear equations. The new methods have high computational efficiency and low computational cost. The order of convergence of the new methods is proved by a development of an inverse first-order divided difference operator. The computational efficiency is compared with the existing methods. Numerical experiments support the theoretical results. Experimental results show that the new methods remarkably reduce the computing time in the process of high-precision computing. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Show Figures

Figure 1

Open AccessEditorial
Algorithms for Managing, Querying and Processing Big Data in Cloud Environments
Algorithms 2016, 9(1), 13; https://doi.org/10.3390/a9010013 - 01 Feb 2016
Cited by 1 | Viewed by 1975
Abstract
Big data (e.g., [1–3]) has become one of the most challenging research topics in current years. Big data is everywhere, from social networks to web advertisements, from sensor and stream systems to bio-informatics, from graph management tools to smart cities, and so forth. [...] Read more.
Big data (e.g., [1–3]) has become one of the most challenging research topics in current years. Big data is everywhere, from social networks to web advertisements, from sensor and stream systems to bio-informatics, from graph management tools to smart cities, and so forth. [...] Full article
Open AccessArticle
Integrating Pareto Optimization into Dynamic Programming
Algorithms 2016, 9(1), 12; https://doi.org/10.3390/a9010012 - 27 Jan 2016
Cited by 2 | Viewed by 2406
Abstract
Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when [...] Read more.
Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when scoring schemes A and B can correctly evaluate the search space via dynamic programming, then so can Pareto optimization with respect to A and B. However, the integration of Pareto optimization into dynamic programming opens a wide range of algorithmic alternatives, which we study in substantial detail in this article, using real-world applications in biosequence analysis, a field where dynamic programming is ubiquitous. Our results are two-fold: (1) We introduce the operation of a “Pareto algebra product” in the dynamic programming framework of Bellman’s GAP. Users of this framework can now ask for Pareto optimization with a single keystroke. Careful evaluation of the implementation alternatives by means of an extended Bellman’s GAP compiler demonstrates the dependence of the best implementation choice on the application at hand. (2) We extract from our experiments several pieces of advice to programmers who do not use a system such as Bellman’s GAP, but who choose to hand-craft their dynamic programming recurrences, incorporating Pareto optimization from scratch. Full article
Show Figures

Figure 1

Open AccessEditorial
Acknowledgement to Reviewers of Algorithms in 2015
Algorithms 2016, 9(1), 11; https://doi.org/10.3390/a9010011 - 22 Jan 2016
Viewed by 1605
Abstract
The editors of Algorithms would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2015. [...] Full article
Open AccessArticle
An Optimal Order Method for Multiple Roots in Case of Unknown Multiplicity
Algorithms 2016, 9(1), 10; https://doi.org/10.3390/a9010010 - 22 Jan 2016
Cited by 1 | Viewed by 1518
Abstract
In the literature, recently, some three-step schemes involving four function evaluations for the solution of multiple roots of nonlinear equations, whose multiplicity is not known in advance, are considered, but they do not agree with Kung–Traub’s conjecture. The present article is devoted to [...] Read more.
In the literature, recently, some three-step schemes involving four function evaluations for the solution of multiple roots of nonlinear equations, whose multiplicity is not known in advance, are considered, but they do not agree with Kung–Traub’s conjecture. The present article is devoted to the study of an iterative scheme for approximating multiple roots with a convergence rate of eight, when the multiplicity is hidden, which agrees with Kung–Traub’s conjecture. The theoretical study of the convergence rate is investigated and demonstrated. A few nonlinear problems are presented to justify the theoretical study. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Open AccessArticle
NBTI-Aware Transient Fault Rate Analysis Method for Logic Circuit Based on Probability Voltage Transfer Characteristics
Algorithms 2016, 9(1), 9; https://doi.org/10.3390/a9010009 - 18 Jan 2016
Cited by 11 | Viewed by 2138
Abstract
The reliability of Very Large Scale Integration (VLSI) circuits has become increasingly susceptible to transient faults induced by environmental noise with the scaling of technology. Some commonly used fault tolerance strategies require statistical methods to accurately estimate the fault rate in different parts [...] Read more.
The reliability of Very Large Scale Integration (VLSI) circuits has become increasingly susceptible to transient faults induced by environmental noise with the scaling of technology. Some commonly used fault tolerance strategies require statistical methods to accurately estimate the fault rate in different parts of the logic circuit, and Monte Carlo (MC) simulation is often applied to complete this task. However, the MC method suffers from impractical computation costs due to the size of the circuits. Furthermore, circuit aging effects, such as negative bias temperature instability (NBTI), will change the characteristics of the circuit during its lifetime, leading to a change in the circuit’s noise margin. This change will increase the complexity of transient fault rate estimation tasks. In this paper, an NBTI-aware statistical analysis method based on probability voltage transfer characteristics is proposed for combinational logic circuit. This method can acquire accurate fault rates using a discrete probability density function approximation process, thus resolving the computation cost problem of the MC method. The proposed method can also consider aging effects and analyze statistical changes in the fault rates. Experimental results demonstrate that, compared to the MC simulation, our method can achieve computation times that are two orders of magnitude shorter while maintaining an error rate less than 9%. Full article
Show Figures

Figure 1

Open AccessArticle
A Greedy Algorithm for Neighborhood Overlap-Based Community Detection
Algorithms 2016, 9(1), 8; https://doi.org/10.3390/a9010008 - 11 Jan 2016
Cited by 13 | Viewed by 3628
Abstract
The neighborhood overlap (NOVER) of an edge u-v is defined as the ratio of the number of nodes who are neighbors for both u and v to that of the number of nodes who are neighbors of at least u or [...] Read more.
The neighborhood overlap (NOVER) of an edge u-v is defined as the ratio of the number of nodes who are neighbors for both u and v to that of the number of nodes who are neighbors of at least u or v. In this paper, we hypothesize that an edge u-v with a lower NOVER score bridges two or more sets of vertices, with very few edges (other than u-v) connecting vertices from one set to another set. Accordingly, we propose a greedy algorithm of iteratively removing the edges of a network in the increasing order of their neighborhood overlap and calculating the modularity score of the resulting network component(s) after the removal of each edge. The network component(s) that have the largest cumulative modularity score are identified as the different communities of the network. We evaluate the performance of the proposed NOVER-based community detection algorithm on nine real-world network graphs and compare the performance against the multi-level aggregation-based Louvain algorithm, as well as the original and time-efficient versions of the edge betweenness-based Girvan-Newman (GN) community detection algorithm. Full article
(This article belongs to the Special Issue Algorithms for Complex Network Analysis)
Show Figures

Figure 1

Open AccessArticle
An Effective and Efficient MapReduce Algorithm for Computing BFS-Based Traversals of Large-Scale RDF Graphs
Algorithms 2016, 9(1), 7; https://doi.org/10.3390/a9010007 - 11 Jan 2016
Cited by 3 | Viewed by 2620
Abstract
Nowadays, a leading instance of big data is represented by Web data that lead to the definition of so-called big Web data. Indeed, extending beyond to a large number of critical applications (e.g., Web advertisement), these data expose several characteristics that [...] Read more.
Nowadays, a leading instance of big data is represented by Web data that lead to the definition of so-called big Web data. Indeed, extending beyond to a large number of critical applications (e.g., Web advertisement), these data expose several characteristics that clearly adhere to the well-known 3V properties (i.e., volume, velocity, variety). Resource Description Framework (RDF) is a significant formalism and language for the so-called Semantic Web, due to the fact that a very wide family of Web entities can be naturally modeled in a graph-shaped manner. In this context, RDF graphs play a first-class role, because they are widely used in the context of modern Web applications and systems, including the emerging context of social networks. When RDF graphs are defined on top of big (Web) data, they lead to the so-called large-scale RDF graphs, which reasonably populate the next-generation Semantic Web. In order to process such kind of big data, MapReduce, an open source computational framework specifically tailored to big data processing, has emerged during the last years as the reference implementation for this critical setting. In line with this trend, in this paper, we present an approach for efficiently implementing traversals of large-scale RDF graphs over MapReduce that is based on the Breadth First Search (BFS) strategy for visiting (RDF) graphs to be decomposed and processed according to the MapReduce framework. We demonstrate how such implementation speeds-up the analysis of RDF graphs with respect to competitor approaches. Experimental results clearly support our contributions. Full article
Show Figures

Figure 1

Open AccessArticle
Efficient Metaheuristics for the Mixed Team Orienteering Problem with Time Windows
Algorithms 2016, 9(1), 6; https://doi.org/10.3390/a9010006 - 05 Jan 2016
Cited by 3 | Viewed by 2235
Abstract
Given a graph whose nodes and edges are associated with a profit, a visiting (or traversing) time and an admittance time window, the Mixed Team Orienteering Problem with Time Windows (MTOPTW) seeks for a specific number of walks spanning a subset of nodes [...] Read more.
Given a graph whose nodes and edges are associated with a profit, a visiting (or traversing) time and an admittance time window, the Mixed Team Orienteering Problem with Time Windows (MTOPTW) seeks for a specific number of walks spanning a subset of nodes and edges of the graph so as to maximize the overall collected profit. The visit of the included nodes and edges should take place within their respective time window and the overall duration of each walk should be below a certain threshold. In this paper we introduce the MTOPTW, which can be used for modeling a realistic variant of the Tourist Trip Design Problem where the objective is the derivation of near-optimal multiple-day itineraries for tourists visiting a destination which features several points of interest (POIs) and scenic routes. Since the MTOPTW is a NP-hard problem, we propose the first metaheuristic approaches to tackle it. The effectiveness of our algorithms is validated through a number of experiments on POI and scenic route sets compiled from the city of Athens (Greece). Full article
Show Figures

Figure 1

Open AccessArticle
A Family of Iterative Methods for Solving Systems of Nonlinear Equations Having Unknown Multiplicity
Algorithms 2016, 9(1), 5; https://doi.org/10.3390/a9010005 - 31 Dec 2015
Cited by 1 | Viewed by 2030
Abstract
The singularity of Jacobian happens when we are looking for a root, with multiplicity greater than one, of a system of nonlinear equations. The purpose of this article is two-fold. Firstly, we will present a modification of an existing method that computes roots [...] Read more.
The singularity of Jacobian happens when we are looking for a root, with multiplicity greater than one, of a system of nonlinear equations. The purpose of this article is two-fold. Firstly, we will present a modification of an existing method that computes roots with known multiplicities. Secondly, will propose the generalization of a family of methods for solving nonlinear equations with unknown multiplicities, to the system of nonlinear equations. The inclusion of a nonzero multi-variable auxiliary function is the key idea. Different choices of the auxiliary function give different families of the iterative method to find roots with unknown multiplicities. Few illustrative numerical experiments and a critical discussion end the paper. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Open AccessArticle
A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm
Algorithms 2016, 9(1), 4; https://doi.org/10.3390/a9010004 - 30 Dec 2015
Cited by 5 | Viewed by 2479
Abstract
Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization. This paper presents a modified GWO algorithm based on [...] Read more.
Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization. This paper presents a modified GWO algorithm based on complex-valued encoding; namely the complex-valued encoding grey wolf optimization (CGWO). We use CGWO to test 16 unconstrained benchmark functions with seven different scales and infinite impulse response (IIR) model identification. Compared to the real-valued GWO algorithm and other optimization algorithms; the CGWO performs significantly better in terms of accuracy; robustness; and convergence speed. Full article
Show Figures

Figure 1

Open AccessArticle
Function Optimization and Parameter Performance Analysis Based on Gravitation Search Algorithm
Algorithms 2016, 9(1), 3; https://doi.org/10.3390/a9010003 - 24 Dec 2015
Cited by 2 | Viewed by 2360
Abstract
The gravitational search algorithm (GSA) is a kind of swarm intelligence optimization algorithm based on the law of gravitation. The parameter initialization of all swarm intelligence optimization algorithms has an important influence on the global optimization ability. Seen from the basic principle of [...] Read more.
The gravitational search algorithm (GSA) is a kind of swarm intelligence optimization algorithm based on the law of gravitation. The parameter initialization of all swarm intelligence optimization algorithms has an important influence on the global optimization ability. Seen from the basic principle of GSA, the convergence rate of GSA is determined by the gravitational constant and the acceleration of the particles. The optimization performances on six typical test functions are verified by the simulation experiments. The simulation results show that the convergence speed of the GSA algorithm is relatively sensitive to the setting of the algorithm parameters, and the GSA parameter can be used flexibly to improve the algorithm’s convergence velocity and improve the accuracy of the solutions. Full article
Show Figures

Figure 1

Open AccessArticle
On the Kung-Traub Conjecture for Iterative Methods for Solving Quadratic Equations
Algorithms 2016, 9(1), 1; https://doi.org/10.3390/a9010001 - 24 Dec 2015
Cited by 3 | Viewed by 2012
Abstract
Kung-Traub’s conjecture states that an optimal iterative method based on d function evaluations for finding a simple zero of a nonlinear function could achieve a maximum convergence order of 2 d−1. During the last years, many attempts have been made to prove [...] Read more.
Kung-Traub’s conjecture states that an optimal iterative method based on d function evaluations for finding a simple zero of a nonlinear function could achieve a maximum convergence order of 2 d−1. During the last years, many attempts have been made to prove this conjecture or develop optimal methods which satisfy the conjecture. We understand from the conjecture that the maximum order reached by a method with three function evaluations is four, even for quadratic functions. In this paper, we show that the conjecture fails for quadratic functions. In fact, we can find a 2-point method with three function evaluations reaching fifth order convergence. We also develop 2-point 3rd to 8th order methods with one function and two first derivative evaluations using weight functions. Furthermore, we show that with the same number of function evaluations we can develop higher order 2-point methods of order r + 2 , where r is a positive integer, ≥ 1 . We also show that we can develop a higher order method with the same number of function evaluations if we know the asymptotic error constant of the previous method. We prove the local convergence of these methods which we term as Babajee’s Quadratic Iterative Methods and we extend these methods to systems involving quadratic equations. We test our methods with some numerical experiments including an application to Chandrasekhar’s integral equation arising in radiative heat transfer theory. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Show Figures

Figure 1

Open AccessArticle
Offset-Assisted Factored Solution of Nonlinear Systems
Algorithms 2016, 9(1), 2; https://doi.org/10.3390/a9010002 - 23 Dec 2015
Viewed by 1721
Abstract
This paper presents an improvement to the recently-introduced factored method for the solution of nonlinear equations. The basic idea consists of transforming the original system by adding an offset to all unknowns. When searching for real solutions, a real offset prevents the intermediate [...] Read more.
This paper presents an improvement to the recently-introduced factored method for the solution of nonlinear equations. The basic idea consists of transforming the original system by adding an offset to all unknowns. When searching for real solutions, a real offset prevents the intermediate values of unknowns from becoming complex. Reciprocally, when searching for complex solutions, a complex offset is advisable to allow the iterative process to quickly abandon the real domain. Several examples are used to illustrate the performance of the proposed algorithm, when compared to Newton’s method. Full article
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop