Scientific Programming
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<p>Scientific Programming is a peer-reviewed, open access journal that provides a meeting ground for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.</p>Hindawi Limiteden-USScientific Programming1058-9244A Matheuristic Approach Combining Local Search and Mathematical Programming
http://www.i-scholar.in/index.php/sp/article/view/98480
A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.Carolina LagosGuillermo GuerreroEnrique CabreraStefanie NiklanderFranklin JohnsonFernando ParedesJorge Vega2016Automatically Produced Algorithms for the Generalized Minimum Spanning Tree Problem
http://www.i-scholar.in/index.php/sp/article/view/98481
The generalized minimum spanning tree problem consists of finding a minimum cost spanning tree in an undirected graph for which the vertices are divided into clusters. Such spanning tree includes only one vertex from each cluster. Despite the diverse practical applications for this problem, the NP-hardness continues to be a computational challenge. Good quality solutions for some instances of the problem have been found by combining specific heuristics or by including them within a metaheuristic. However studied combinations correspond to a subset of all possible combinations. In this study a technique based on a genotypephenotype genetic algorithmto automatically construct new algorithms for the problem, which contain combinations of heuristics, is presented. The produced algorithms are competitive in terms of the quality of the solution obtained. This emerges from the comparison of the performance with problem-specific heuristics and with metaheuristic approaches.Carlos Contreras-BoltonCarlos ReySergio Ramos-CossioClaudio RodriguezFelipe GaticaVictor Parada2016Racing Sampling based Microimmune Optimization Approach Solving Constrained Expected Value Programming
http://www.i-scholar.in/index.php/sp/article/view/98482
This work investigates a bioinspired microimmune optimization algorithm to solve a general kind of single-objective nonlinear constrained expected value programming without any prior distribution. In the study of algorithm, two lower bound sample estimates of random variables are theoretically developed to estimate the empirical values of individuals. Two adaptive racing sampling schemes are designed to identify those competitive individuals in a given population, by which high-quality individuals can obtain large sampling size. An immune evolutionary mechanism, along with a local search approach, is constructed to evolve the current population. The comparative experiments have showed that the proposed algorithm can effectively solve higherdimensional benchmark problems and is of potential for further applications.Kai YangZhuhong Zhang2016HSIP: A Novel Task Scheduling Algorithm for Heterogeneous Computing
http://www.i-scholar.in/index.php/sp/article/view/98483
High-performance heterogeneous computing systems are achieved by the use of efficient application scheduling algorithms. However, most of the current algorithms have low efficiency in scheduling. Aiming at solving this problem, we propose a novel task scheduling algorithm for heterogeneous computing named HSIP (heterogeneous scheduling algorithm with improved task priority) whose functionality relies on three pillars: (1) an improved task priority strategy based on standard deviation with improved magnitude as computation weight and communication cost weight to make scheduling priority more reasonable; (2) an entry task duplication selection policy to make the makespan shorter; and (3) an improved idle time slots (ITS) insertion-based optimizing policy to make the task scheduling more efficient.We evaluate our proposed algorithm on randomly generated DAGs, using some real application DAGs by comparison with some classical scheduling algorithms. According to the experimental results, our proposed algorithm appears to perform better than other algorithms in terms of schedule length ratio, efficiency, and frequency of best results.Guan WangYuxin WangHui LiuHe Guo2016A Topic Space Oriented User Group Discovering Scheme in Social Network: A Trust Chain based Interest Measuring Perspective
http://www.i-scholar.in/index.php/sp/article/view/98484
Currently, user group has become an effective platform for information sharing and communicating among users in social network sites. In present work, we propose a single topic user group discovering scheme, which includes three phases: topic impact evaluation, interest degree measurement, and trust chain based discovering, to enable selecting influential topic and discovering users into a topic oriented group. Our main works include (1) an overview of proposed scheme and its related definitions; (2) topic space construction method based on topic relatedness clustering and its impact (influence degree and popularity degree) evaluation; (3) a trust chain model to take user relation network topological information into account with a strength classification perspective; (4) an interest degree (user explicit and implicit interest degree) evaluation method based on trust chain among users; and (5) a topic space oriented user group discovering method to group core users according to their explicit interest degrees and to predict ordinary users under implicit interest and user trust chain. Finally, experimental results are given to explain effectiveness and feasibility of our scheme.Dong WangPeng WangMeizi LiBo Zhang2016AntStar: Enhancing Optimization Problems by Integrating an Ant System and A* Algorithm
http://www.i-scholar.in/index.php/sp/article/view/98485
Recently, nature-inspired techniques have become valuable to many intelligent systems in different fields of technology and science. Among these techniques, Ant Systems (AS) have become a valuable technique for intelligent systems in different fields. AS is a computational system inspired by the foraging behavior of ants and intended to solve practical optimization problems. In this paper, we introduce the AntStar algorithm, which is swarm intelligence based. AntStar enhances the optimization and performance of an AS by integrating the AS and A* algorithm. Applying the AntStar algorithm to the single-source shortest-path problem has been done to ensure the efficiency of the proposed AntStar algorithm.The experimental result of the proposed algorithm illustrated the robustness and accuracy of the AntStar algorithm.Mohammed FaisalHassan MathkourMansour Alsulaiman2016Virtual Machine Placement Algorithm for both Energy-awareness and SLA Violation Reduction in Cloud Data Centers
http://www.i-scholar.in/index.php/sp/article/view/98486
The problem of high energy consumption is becoming more and more serious due to the construction of large-scale cloud data centers. In order to reduce the energy consumption and SLA violation, a new virtual machine (VM) placement algorithm named ATEA (adaptive three-threshold energy-aware algorithm), which takes good use of the historical data from resource usage by VMs, is presented. In ATEA, according to the load handled, data center hosts are divided into four classes: hosts with little load, hosts with light load, hosts with moderate load, and hosts with heavy load. ATEA migrates VMs on heavily loaded or little-loaded hosts to lightly loaded hosts, while the VMs on lightly loaded and moderately loaded hosts remain unchanged. Then, on the basis of ATEA, two kinds of adaptive three-threshold algorithm and three kinds of VMs selection policies are proposed. Finally, we verify the effectiveness of the proposed algorithms by CloudSim toolkit utilizing real-world workload.The experimental results show that the proposed algorithms efficiently reduce energy consumption and SLA violation.Zhou ZhouZhigang HuKeqin Li2016WSF2: A Novel Framework for Filtering Web Spam
http://www.i-scholar.in/index.php/sp/article/view/98487
Over the last years, research on web spam filtering has gained interest from both academia and industry. In this context, although there are a good number of successful antispam techniques available (i.e., content-based, link-based, and hiding), an adequate combination of different algorithms supported by an advanced web spam filtering platform would offer more promising results. To this end, we propose the WSF2 framework, a new platform particularly suitable for filtering spam content on web pages. Currently, our framework allows the easy combination of different filtering techniques including, but not limited to, regular expressions and well-known classifiers (i.e., Naive Bayes, Support Vector Machines, and C5.0). Applying our WSF2 framework over the publicly available WEBSPAM-UK2007 corpus, we have been able to demonstrate that a simple combination of different techniques is able to improve the accuracy of single classifiers on web spam detection. As a result, we conclude that the proposed filtering platform is a powerful tool for boosting applied research in this area.J. Fdez-GlezD. Ruano-OrdasR. LazaJ. R. MendezR. PavonF. Fdez-Riverola2016The Intelligence of Octagonal Fuzzy Number to Determine the Fuzzy Critical Path: a New Ranking Method
http://www.i-scholar.in/index.php/sp/article/view/98488
This research paper proposes a modified ranking approach to determine the critical path in fuzzy project network, where the duration of each activity time is represented by an octagonal fuzzy number. In this method, a modified subtraction formula is carried out on fuzzy numbers. This modified method works well on fuzzy backward pass calculations as there will be no negative time. The analysis is expected to show that the fuzzy number which is used in this paper is more effective in determining the critical path in a fuzzy project network and possibility of meeting the project time. A numerical example is given and compared with trapezoidal, triangular fuzzy numbers through proposed ranking method.S. NarayanamoorthyS. Maheswari2016Equalization Technique for Balancing the Modulation Ratio Characteristics of the Single-Phase-to-Three-Phase Matrix Converter
http://www.i-scholar.in/index.php/sp/article/view/98489
Three-phase system has numerous advantages over the single-phase system in terms of instantaneous power, stability, and cost. Three-phase systems are not available in every location particularly in remote rural areas, hill stations, low voltage distribution homes, and so forth. Having a system that is capable of converting directly the readily available single-phase system to three phases will have greater usability in various applications. The routine techniques adopted in the direct ac-ac single-phase-to-three-phase converters do not yield the best desired outputs because of their complexity in the segregation process and bidirectional nature of the input signal. Other initiatives use ac-dc-ac converters which are huge and costly due to dc link energy storage devices. Further, none of these systems provide a convincing result in producing the standard three-phase output voltages that are 120° away from each other. This paper proposes an effective direct ac-ac single-phase-to-three-phase conversion technique based on space vector pulse width modulation based matrix converter system that produces a convincing three-phase output signals from a single-phase source with balanced modulation index characteristics. The details of the scientific programming adopted on the proposed technique were presented.Vengadeshwaran VeluNorman MariunMohd Amran Mohd RadziNashiren Farzilah Mailah2016Feedback-Based Resource Allocation in MapReduce-Based Systems
http://www.i-scholar.in/index.php/sp/article/view/98490
Containers are considered an optimized fine-grain alternative to virtual machines in cloud-based systems. Some of the approaches which have adopted the use of containers are the MapReduce frameworks. This paper makes an analysis of the use of containers in MapReduce-based systems, concluding that the resource utilization of these systems in terms of containers is suboptimal. In order to solve this, the paper describes AdaptCont, a proposal for optimizing the containers allocation in MapReduce systems. AdaptCont is based on the foundations of feedback systems. Two different selection approaches, Dynamic AdaptCont and Pool AdaptCont, are defined.Whereas Dynamic AdaptCont calculates the exact amount of resources per each container, Pool AdaptCont chooses a predefined container from a pool of available configurations. AdaptCont is evaluated for a particular case, the application master container of Hadoop YARN. As we can see in the evaluation, AdaptCont behaves much better than the default resource allocation mechanism of Hadoop YARN.Bunjamin MemishiMaria S. PerezGabriel Antoniu2016Efficient Parallel Sorting for Migrating Birds Optimization when Solving Machine-Part Cell formation Problems
http://www.i-scholar.in/index.php/sp/article/view/98491
The Machine-Part Cell Formation Problem (MPCFP) is a NP-Hard optimization problem that consists in grouping machines and parts in a set of cells, so that each cell can operate independently and the intercell movements are minimized. This problem has largely been tackled in the literature by using different techniques ranging from classic methods such as linear programming to more modern nature-inspired metaheuristics. In this paper, we present an efficient parallel version of the Migrating Birds Optimization metaheuristic for solving the MPCFP. Migrating Birds Optimization is a population metaheuristic based on the V-Flight formation of the migrating birds, which is proven to be an effective formation in energy saving.This approach is enhanced by the smart incorporation of parallel procedures that notably improve performance of the several sorting processes performed by the metaheuristic. We perform computational experiments on 1080 benchmarks resulting from the combination of 90 well-known MPCFP instances with 12 sorting configurations with and without threads. We illustrate promising results where the proposal is able to reach the global optimum in all instances, while the solving time with respect to a nonparallel approach is notably reduced.Ricardo SotoBroderick CrawfordBoris AlmonacidFernando Paredes2016Energy-Efficient Reliability-Aware Scheduling Algorithm on Heterogeneous Systems
http://www.i-scholar.in/index.php/sp/article/view/98492
The amount of energy needed to operate high-performance computing systems increases regularly since some years at a high pace, and the energy consumption has attracted a great deal of attention. Moreover, high energy consumption inevitably contains failures and reduces system reliability. However, there has been considerably less work of simultaneous management of system performance, reliability, and energy consumption on heterogeneous systems. In this paper, we first build the precedence-constrained parallel applications and energy consumption model. Then, we deduce the relation between reliability and processor frequencies and get their parameters approximation value by least squares curve fitting method. Thirdly, we establish a task execution reliability model and formulate this reliability and energy aware scheduling problem as a linear programming. Lastly, we propose a heuristic Reliability-Energy Aware Scheduling (REAS) algorithm to solve this problem, which can get good tradeoff among system performance, reliability, and energy consumption with lower complexity. Our extensive simulation performance evaluation study clearly demonstrates the tradeoff performance of our proposed heuristic algorithm.Xiaoyong TangWeizhen Tan2016