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Journal articles on the topic 'Large Scale Probleme'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Ahrens, Gerd-Axel, Klaus J. Beckmann, Manfred Boltze, Alexander Eisenkopf, Hartmut Fricke, Günther Knieps, Andreas Knorr, et al. "Auswahl und Abwicklung von Großprojekten/Selection and Execution of large-scale projects." Bauingenieur 90, no. 03 (2015): 129–39. http://dx.doi.org/10.37544/0005-6650-2015-03-63.

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In der Öffentlichkeit entsteht aufgrund von Kostensteigerungen und Zeitverzügen oft der Eindruck, die hoch geschätzte Ingenieurskunst in Deutschland ginge verloren. Tatsächliche Ursachen für die Probleme sind aber oft Verzögerungen in den Phasen der strategischen Planung durch Abstimmungsprozesse mit Maximalforderungen, langwierige politische Grundsatzdebatten mit Blockaden notwendiger Entscheidungen oder Verzögerungen bei der Finanzierung und Mittelbereitstellung, der Projektplanung und deren rechtlichen Sicherung bzw. Genehmigung. Darüber hinaus steht bei Einigen eine grundsätzliche Skepsis gegenüber Großprojekten im Hintergrund, die manchmal mit einer partiellen Innovations-, Technik- und Veränderungsfeindlichkeit gepaart ist. Dabei sind sowohl überzogene Egoismen („Nimby-Effekte“) als auch tatsächlich hohe belastende Wirkungen für Betroffene zu beobachten. Ein weiterer Anlass für Kritik betrifft solche öffentliche Projekte, die oft aus lokalpolitischem Geltungsdrang und Prestigegründen oder mit deutlich überzogenen Nutzenerwartungen (Image, Standortmarketing, Wirtschaftsförderung) hoch subventioniert und ohne hinreichende Effizienznachweise politisch beschlossen und umgesetzt werden.   Der Beitrag zeigt Problemursachen auf und beschreibt Möglichkeiten zur frühzeitigen Identifikation und Problembeseitigung. Dazu zählen klare Definitionen der Projektziele und des Zeitrahmens, der adäquate Umgang mit Unsicherheiten und Risiken, die Qualitätssicherung für Entscheidungen und Prozesse, die Bereitstellung ausreichender Ressourcen, die Vermeidung von Umplanungen während der Bauabwicklung, die Schaffung klarer Verantwortlichkeiten und Haftungsregelungen, die Verbesserung von Kommunikation und Partizipation sowie von Datengrundlagen und Instrumenten.

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P.Sumathi, P. Sumathi, and A. Gangadharan A.Gangadharan. "New Technique to DetectRedundant Constraints in Large Scale Linear Programming Problems." International Journal of Scientific Research 3, no. 6 (June 1, 2012): 236–38. http://dx.doi.org/10.15373/22778179/june2014/77.

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3

MUKADDES, A. M. M., Masao OGINO, Ryuji SHIOYA, and Hiroshi KANAYAMA. "704 A Scalable Balancing Domain Decomposition Based Preconditioner for Large Scale Thermal-Solid Coupling Problems." Proceedings of The Computational Mechanics Conference 2005.18 (2005): 523–24. http://dx.doi.org/10.1299/jsmecmd.2005.18.523.

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4

Mazhar, Hammad, Dan Negrut, Arman Pazouki, and Alessandro Tasora. "59079 A SCALABLE PARALLEL METHOD FOR LARGE SCALE COLLISION DETECTION PROBLEMS(Contact, Impact, and Friction)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _59079–1_—_59079–12_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._59079-1_.

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5

Vakhnin, A. V., E. A. Sopov, I. A. Panfilov, A. S. Polyakova, and D. V. Kustov. "A problem decomposition approach for large-scale global optimization problems." IOP Conference Series: Materials Science and Engineering 537 (June 18, 2019): 052031. http://dx.doi.org/10.1088/1757-899x/537/5/052031.

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6

CONLON, JOSEPH P. "HIERARCHY PROBLEMS IN STRING THEORY AND LARGE VOLUME MODELS." Modern Physics Letters A 23, no. 01 (January 10, 2008): 1–16. http://dx.doi.org/10.1142/s0217732308025930.

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Nature generates many hierarchically different scales. It is necessary to explain where these scales come from and how they are related. Three such scales are the weak scale, the scale associated with axion physics, and the scale associated with neutrino masses. I review the large volume models that arise in flux compactifications of type IIB string theory and explain how an intermediate string scale can quantitatively explain the above three scales. The models also predict a new physical scale at 1 MeV, associated to a gravitationally coupled scalar.

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Banihashemi, Mohamadreza, and Ali Haghani. "Optimization Model for Large-Scale Bus Transit Scheduling Problems." Transportation Research Record: Journal of the Transportation Research Board 1733, no. 1 (January 2000): 23–30. http://dx.doi.org/10.3141/1733-04.

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A procedure is presented for solving real-world large-scale multiple depot vehicle scheduling (MDVS) problems considering the route time constraints (RTCs). The procedure is applied to some test problems and then to a real-world problem. The real-world problem is the transit bus scheduling problem of the mass transit administration (MTA) in Baltimore, Maryland. The RTCs are added to the MDVS problem to account for real-world operational restrictions such as fuel consumption. Formulation of the MDVS problem, the set of constraints for considering the time restriction, and a heuristic procedure for solving the MDVS problems with RTCs are discussed. Application of the proposed procedures in solving bus scheduling problems in large cities requires a reduction in size of those problems in terms of number of variables and constraints. Two techniques are proposed to decrease the size of the real-world problems. Combining these techniques results in a strategy to reduce the MTA problem size into a manageable and solvable size. The solutions to the reduced size problems are further improved by solving a series of single depot vehicle scheduling problems for each of the MTA depots. The final results from the proposed model are compared with the MTA’s January 1998 schedule. The comparison indicates that the proposed model improves on the MTA schedules in all aspects. The improvements are 7.90 percent in the number of vehicles, 4.66 percent in the operational time, and 5.77 percent in the total cost.

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8

Bredereck, Robert, Piotr Faliszewski, Rolf Niedermeier, and Nimrod Talmon. "Large-Scale Election Campaigns: Combinatorial Shift Bribery." Journal of Artificial Intelligence Research 55 (March 16, 2016): 603–52. http://dx.doi.org/10.1613/jair.4927.

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We study the complexity of a combinatorial variant of the Shift Bribery problem in elections. In the standard Shift Bribery problem, we are given an election where each voter has a preference order over the set of candidates and where an outside agent, the briber, can pay each voter to rank the briber's favorite candidate a given number of positions higher. The goal is to ensure the victory of the briber's preferred candidate. The combinatorial variant of the problem, introduced in this paper, models settings where it is possible to affect the position of the preferred candidate in multiple votes, either positively or negatively, with a single bribery action. This variant of the problem is particularly interesting in the context of large-scale campaign management problems (which, from the technical side, are modeled as bribery problems). We show that, in general, the combinatorial variant of the problem is highly intractable; specifically, NP-hard, hard in the parameterized sense, and hard to approximate. Nevertheless, we provide parameterized algorithms and approximation algorithms for natural restricted cases.

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9

Gratch, J., and S. Chien. "Adaptive Problem-solving for Large-scale Scheduling Problems: A Case Study." Journal of Artificial Intelligence Research 4 (May 1, 1996): 365–96. http://dx.doi.org/10.1613/jair.177.

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Although most scheduling problems are NP-hard, domain specific techniques perform well in practice but are quite expensive to construct. In adaptive problem-solving solving, domain specific knowledge is acquired automatically for a general problem solver with a flexible control architecture. In this approach, a learning system explores a space of possible heuristic methods for one well-suited to the eccentricities of the given domain and problem distribution. In this article, we discuss an application of the approach to scheduling satellite communications. Using problem distributions based on actual mission requirements, our approach identifies strategies that not only decrease the amount of CPU time required to produce schedules, but also increase the percentage of problems that are solvable within computational resource limitations.

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10

Jagers, Sverker C., Niklas Harring, Åsa Löfgren, Martin Sjöstedt, Francisco Alpizar, Bengt Brülde, David Langlet, et al. "On the preconditions for large-scale collective action." Ambio 49, no. 7 (November 12, 2019): 1282–96. http://dx.doi.org/10.1007/s13280-019-01284-w.

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Abstract The phenomenon of collective action and the origin of collective action problems have been extensively and systematically studied in the social sciences. Yet, while we have substantial knowledge about the factors promoting collective action at the local level, we know far less about how these insights travel to large-scale collective action problems. Such problems, however, are at the heart of humanity’s most pressing challenges, including climate change, large-scale natural resource depletion, biodiversity loss, nuclear proliferation, antibiotic resistance due to overconsumption of antibiotics, and pollution. In this paper, we suggest an analytical framework that captures the theoretical understanding of preconditions for large-scale collective action. This analytical framework aims at supporting future empirical analyses of how to cope with and overcome larger-scale collective action problems. More specifically, we (i) define and describe the main characteristics of a large-scale collective action problem and (ii) explain why voluntary and, in particular, spontaneous large-scale collective action among individual actors becomes more improbable as the collective action problem becomes larger, thus demanding interventions by an external authority (a third party) for such action to be generated. Based on this, we (iii) outline an analytical framework that illustrates the connection between third-party interventions and large-scale collective action. We conclude by suggesting avenues for future research.

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Ain, Qura, and Ji-Huan He. "On two-scale dimension and its applications." Thermal Science 23, no. 3 Part B (2019): 1707–12. http://dx.doi.org/10.2298/tsci190408138a.

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Dimension or scale is everything. When a thing is observed by different scales, different results can be obtained. Two scales are enough for most of practical problems, and a new definition of a two-scale dimension instead of the fractal dimension is given to deal with discontinuous problems. Fractal theory considers a self-similarity pattern, which cannot be found in any a real problem, while the two-scale theory observes each problem with two scales, the large scale is for an approximate continuous problem, where the classic calculus can be fully applied, and on the smaller scale, the effect of the porous structure on the properties can be easily elucidated. This paper sheds a new light on applications of fractal theory to real problems.

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NEIL, MARTIN, NORMAN FENTON, and LARS NIELSON. "Building large-scale Bayesian networks." Knowledge Engineering Review 15, no. 3 (September 2000): 257–84. http://dx.doi.org/10.1017/s0269888900003039.

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Bayesian networks (BNs) model problems that involve uncertainty. A BN is a directed graph, whose nodes are the uncertain variables and whose edges are the causal or influential links between the variables. Associated with each node is a set of conditional probability functions that model the uncertain relationship between the node and its parents. The benefits of using BNs to model uncertain domains are well known, especially since the recent breakthroughs in algorithms and tools to implement them. However, there have been serious problems for practitioners trying to use BNs to solve realistic problems. This is because, although the tools make it possible to execute large-scale BNs efficiently, there have been no guidelines on building BNs. Specifically, practitioners face two significant barriers. The first barrier is that of specifying the graph structure such that it is a sensible model of the types of reasoning being applied. The second barrier is that of eliciting the conditional probability values. In this paper we concentrate on this first problem. Our solution is based on the notion of generally applicable “building blocks”, called idioms, which serve solution patterns. These can then in turn be combined into larger BNs, using simple combination rules and by exploiting recent ideas on modular and object oriented BNs (OOBNs). This approach, which has been implemented in a BN tool, can be applied in many problem domains. We use examples to illustrate how it has been applied to build large-scale BNs for predicting software safety. In the paper we review related research from the knowledge and software engineering literature. This provides some context to the work and supports our argument that BN knowledge engineers require the same types of processes, methods and strategies enjoyed by systems and software engineers if they are to succeed in producing timely, quality and cost-effective BN decision support solutions.

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13

Cai, Liang-Wu, and James H. Williams. "Large-scale multiple scattering problems." Ultrasonics 37, no. 7 (November 1999): 453–62. http://dx.doi.org/10.1016/s0041-624x(99)00029-3.

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14

Nishimura, Naoshi, and Ken Hayami. "Large scale problems using BEM." Engineering Analysis with Boundary Elements 27, no. 5 (May 2003): 403. http://dx.doi.org/10.1016/s0955-7997(02)00151-0.

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15

Kerner, W. "Large-scale complex eigenvalue problems." Journal of Computational Physics 85, no. 1 (November 1989): 1–85. http://dx.doi.org/10.1016/0021-9991(89)90200-3.

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16

Chen, Chen, Ruiyue Peng, Lei Ying, and Hanghang Tong. "Fast Connectivity Minimization on Large-Scale Networks." ACM Transactions on Knowledge Discovery from Data 15, no. 3 (May 2021): 1–25. http://dx.doi.org/10.1145/3442342.

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The connectivity of networks has been widely studied in many high-impact applications, ranging from immunization, critical infrastructure analysis, social network mining, to bioinformatic system studies. Regardless of the end application domains, connectivity minimization has always been a fundamental task to effectively control the functioning of the underlying system. The combinatorial nature of the connectivity minimization problem imposes an exponential computational complexity to find the optimal solution, which is intractable in large systems. To tackle the computational barrier, greedy algorithm is extensively used to ensure a near-optimal solution by exploiting the diminishing returns property of the problem. Despite the empirical success, the theoretical and algorithmic challenges of the problems still remain wide open. On the theoretical side, the intrinsic hardness and the approximability of the general connectivity minimization problem are still unknown except for a few special cases. On the algorithmic side, existing algorithms are hard to balance between the optimization quality and computational efficiency. In this article, we address the two challenges by (1) proving that the general connectivity minimization problem is NP-hard and is the best approximation ratio for any polynomial algorithms, and (2) proposing the algorithm CONTAIN and its variant CONTAIN + that can well balance optimization effectiveness and computational efficiency for eigen-function based connectivity minimization problems in large networks.

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17

Aubin, Jean, and Jacques A. Ferland. "A large scale timetabling problem." Computers & Operations Research 16, no. 1 (January 1989): 67–77. http://dx.doi.org/10.1016/0305-0548(89)90053-1.

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18

Lim, Kai H., and Scott R. Swenseth. "An iterative procedure for reducing problem size in large scale AHP problems." European Journal of Operational Research 67, no. 1 (May 1993): 64–74. http://dx.doi.org/10.1016/0377-2217(93)90322-e.

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19

Zheng, Yongbin, Yuzhuang Yan, Sheng Liu, Xinsheng Huang, and Wanying Xu. "An Efficient Approach to Solve the Large-Scale Semidefinite Programming Problems." Mathematical Problems in Engineering 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/764760.

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Solving the large-scale problems with semidefinite programming (SDP) constraints is of great importance in modeling and model reduction of complex system, dynamical system, optimal control, computer vision, and machine learning. However, existing SDP solvers are of large complexities and thus unavailable to deal with large-scale problems. In this paper, we solve SDP using matrix generation, which is an extension of the classical column generation. The exponentiated gradient algorithm is also used to solve the special structure subproblem of matrix generation. The numerical experiments show that our approach is efficient and scales very well with the problem dimension. Furthermore, the proposed algorithm is applied for a clustering problem. The experimental results on real datasets imply that the proposed approach outperforms the traditional interior-point SDP solvers in terms of efficiency and scalability.

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20

Blouin, Vincent Y., Michael M. Bernitsas, and Denby Morrison. "Integrated Redesign of Large-Scale Structures by Large Admissible Perturbations." Journal of Offshore Mechanics and Arctic Engineering 125, no. 4 (October 1, 2003): 234–41. http://dx.doi.org/10.1115/1.1596236.

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In structural redesign (inverse design), selection of the number and type of performance constraints is a major challenge. This issue is directly related to the computational effort and, most importantly, to the success of the optimization solver in finding a solution. These issues are the focus of this paper, which provides and discusses techniques that can help designers formulate a well-posed integrated complex redesign problem. LargE Admissible Perturbations (LEAP) is a general methodology, which solves redesign problems of complex structures with, among others, free vibration, static deformation, and forced response amplitude constraints. The existing algorithm, referred to as the Incremental Method is improved in this paper for problems with static and forced response amplitude constraints. This new algorithm, referred to as the Direct Method, offers comparable level of accuracy for less computational time and provides robustness in solving large-scale redesign problems in the presence of damping, nonstructural mass, and fluid-structure interaction effects. Common redesign problems include several natural frequency constraints and forced response amplitude constraints at various frequencies of excitation. Several locations on the structure and degrees of freedom can be constrained simultaneously. The designer must exercise judgment and physical intuition to limit the number of constraints and consequently the computational time. Strategies and guidelines are discussed. Such techniques are presented and applied to a 2,694 degree of freedom offshore tower.

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V.P., Sakthivel, Suman M., and Sathya P.D. "Large-scale economic load dispatch using squirrel search algorithm." International Journal of Energy Sector Management 14, no. 6 (July 3, 2020): 1351–80. http://dx.doi.org/10.1108/ijesm-02-2020-0012.

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Purpose Economic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants. Design/methodology/approach The suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately. Findings Empirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems. Practical implications This study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning. Originality/value To the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

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Chu, Hai D., Eric Gelman, and Ellis L. Johnson. "Solving large scale crew scheduling problems." European Journal of Operational Research 97, no. 2 (March 1997): 260–68. http://dx.doi.org/10.1016/s0377-2217(96)00196-8.

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23

Huy Phan, Anh, and Andrzej Cichocki. "PARAFAC algorithms for large-scale problems." Neurocomputing 74, no. 11 (May 2011): 1970–84. http://dx.doi.org/10.1016/j.neucom.2010.06.030.

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24

Jarrah, Ahmad I. Z., Jonathan F. Bard, and Anura H. deSilva. "Solving Large-Scale Tour Scheduling Problems." Management Science 40, no. 9 (September 1994): 1124–44. http://dx.doi.org/10.1287/mnsc.40.9.1124.

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Meek, J. L. "Solving large scale problems in mechanics." Computing Systems in Engineering 5, no. 3 (June 1994): 295. http://dx.doi.org/10.1016/0956-0521(94)90009-4.

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26

Derigs, U., and A. Metz. "Solving (large scale) matching problems combinatorially." Mathematical Programming 50, no. 1-3 (March 1991): 113–21. http://dx.doi.org/10.1007/bf01594929.

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Hermann, Peter. "Solving large-scale problems in mechanics." Computer Methods in Applied Mechanics and Engineering 114, no. 1-2 (April 1994): 189–90. http://dx.doi.org/10.1016/0045-7825(94)90169-4.

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Bai, Zhaojun, Gark Fahey, and Gene Golub. "Some large-scale matrix computation problems." Journal of Computational and Applied Mathematics 74, no. 1-2 (November 1996): 71–89. http://dx.doi.org/10.1016/0377-0427(96)00018-0.

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29

Chen, Yuzhong, Yang Yu, and Guolong Chen. "Shortest distance estimation in large scale graphs." Engineering Computations 31, no. 8 (October 28, 2014): 1635–47. http://dx.doi.org/10.1108/ec-11-2012-0286.

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Purpose – Shortest distance query between a pair of nodes in a graph is a classical problem with a wide variety of applications. Exact methods for this problem are infeasible for large-scale graphs such as social networks with hundreds of millions of users and links due to their high complexity of time and space. The purpose of this paper is to propose a novel landmark selection strategy which can estimate the shortest distances in large-scale graphs and clarify the efficiency and accuracy of the proposed strategy in comparison with currently used strategies. Design/methodology/approach – Different from existing strategies, the landmark selection problem is regarded as a binary combinational optimization problem consisting of two optimization objectives and one constraint. Further, the original binary combinational optimization problem with constraints is transformed to a proper form of optimization objectives without any additional constraints and the equivalence of solutions is proved. Finally the solution of the optimization problem is performed with a modified multi-objective particle swarm optimization (MOPSO) integrating the mutation operator and crossover operator of genetic algorithm. Findings – Four real networks of large scale are used as data sets to carry out the experiments and the experiment results show that the proposed strategy improves both of the accuracy and time efficiency to perform shortest distance estimation in large scale graph compared to other currently used strategies. Originality/value – This paper proposes a novel landmark selection strategy which regards the landmark selection problem as a binary combinational optimization problem. The original binary combinational optimization problem with constraints is transformed to a proper form of optimization objectives without constraints and the equivalence of these two optimization problems is proved. This novel strategy also utilizes a modified MOPSO integrating the mutation operator and crossover operator of genetic algorithm.

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Li, Feiyue, Bruce Golden, and Edward Wasil. "The open vehicle routing problem: Algorithms, large-scale test problems, and computational results." Computers & Operations Research 34, no. 10 (October 2007): 2918–30. http://dx.doi.org/10.1016/j.cor.2005.11.018.

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Zheng, Min Juan, Guo Jian Cheng, and Fei Zhao. "Large-Scale Data Classification Based on Ball Vector Machine." Applied Mechanics and Materials 312 (February 2013): 771–76. http://dx.doi.org/10.4028/www.scientific.net/amm.312.771.

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The quadratic programming problem in the standard support vector machine (SVM) algorithm has high time complexity and space complexity in solving the large-scale problems which becomes a bottleneck in the SVM applications. Ball Vector Machine (BVM) converts the quadratic programming problem of the traditional SVM into the minimum enclosed ball problem (MEB). It can indirectly get the solution of quadratic programming through solving the MEB problem which significantly reduces the time complexity and space complexity. The experiments show that when handling five large-scale and high-dimensional data sets, the BVM and standard SVM have a considerable accuracy, but the BVM has higher speed and less requirement space than standard SVM.

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Prives, Leslie. "Applying small-scale solutions to large-scale problems [Amperes]." IEEE Women in Engineering Magazine 2, no. 2 (2008): 4–5. http://dx.doi.org/10.1109/mwe.2008.930538.

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Yan, Danping, and Yongzhong Lu. "Recent Advances in Particle Swarm Optimization for Large Scale Problems." Journal of Autonomous Intelligence 1, no. 1 (October 14, 2018): 22. http://dx.doi.org/10.32629/jai.v1i1.15.

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Accompanied by the advent of current big data ages, the scales of real world optimization problems with many decisive design variables are becoming much larger. Up to date, how to develop new optimization algorithms for these large scale problems and how to expand the scalability of existing optimization algorithms have posed further challenges in the domain of bio-inspired computation. So addressing these complex large scale problems to produce truly useful results is one of the presently hottest topics. As a branch of the swarm intelligence based algorithms, particle swarm optimization (PSO) for coping with large scale problems and its expansively diverse applications have been in rapid development over the last decade years. This review paper mainly presents its recent achievements and trends, and also highlights the existing unsolved challenging problems and key issues with a huge impact in order to encourage further more research in both large scale PSO theories and their applications in the forthcoming years.

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Militello, Laura G., Emily S. Patterson, Robert Wears, and Jill A. Ritter. "Large-Scale Coordination in Emergency Response." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 3 (September 2005): 534–38. http://dx.doi.org/10.1177/154193120504900368.

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Coordination is a key element in emergency response. This paper focuses on coordination as it occurred in a county-level Emergency Operations Center (EOC) during a simulated tornado. The EOC is responsible for locating, purchasing, and transporting resources to the disaster scene(s). The EOC is an ad hoc team made up of government agencies, private companies (i.e., hospitals, utilities, etc.), and non-governmental agencies. These decision makers come together to engage in creative problem solving in order to solve often complex logistics and coordination problems generally under intense time pressure during a rapidly evolving situation. Lessons learned from this exercise highlight coordination challenges including asymmetric information flow, natural fault lines, roles and functions, co-location benefits, emergent leadership, fragmented situation awareness, information displays, room design, and quick reference tools.

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Ursani, Ziauddin, Daryl Essam, David Cornforth, and Robert Stocker. "Enhancements to the Localized Genetic Algorithm for Large Scale Capacitated Vehicle Routing Problems." International Journal of Applied Evolutionary Computation 4, no. 1 (January 2013): 17–38. http://dx.doi.org/10.4018/jaec.2013010102.

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This paper is a continuation of two previous papers where the authors used Genetic Algorithm with automated problem decomposition strategy for small scale capacitated vehicle routing problems (CVRP) and vehicle routing problem with time windows (VRPTW). In this paper they have extended their scheme to large scale capacitated vehicle routing problems by introducing selective search version of the automated problem decomposition strategy, a faster genotype to phenotype translation scheme, and various search reduction techniques. The authors have shown that genetic algorithm used with automated problem decomposition strategy outperforms the GAs applied on the problem as a whole not only in terms of solution quality but also in terms of computational time on the large scale problems.

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Berry, Michael W. "Large-Scale Sparse Singular Value Computations." International Journal of Supercomputing Applications 6, no. 1 (April 1992): 13–49. http://dx.doi.org/10.1177/109434209200600103.

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We present four numerical methods for computing the singular value decomposition (SVD) of large sparse matrices on a multiprocessor architecture. We emphasize Lanczos and subspace iteration-based methods for determining several of the largest singular triplets (singular values and corresponding left- and right-singular vectors) for sparse matrices arising from two practical applications: information retrieval and seismic reflection tomography. The target architectures for our implementations are the CRAY-2S/4–128 and Alliant FX/80. The sparse SVD problem is well motivated by recent information-retrieval techniques in which dominant singular values and their corresponding singular vectors of large sparse term-document matrices are desired, and by nonlinear inverse problems from seismic tomography applications which require approximate pseudo-inverses of large sparse Jacobian matrices. This research may help advance the development of future out-of-core sparse SVD methods, which can be used, for example, to handle extremely large sparse matrices 0 × (106) rows or columns associated with extremely large databases in query-based information-retrieval applications.

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37

SCHAUER, MARCO, SABINE LANGER, JOSE E. ROMAN, and ENRIQUE S. QUINTANA-ORTÍ. "LARGE SCALE SIMULATION OF WAVE PROPAGATION IN SOILS INTERACTING WITH STRUCTURES USING FEM AND SBFEM." Journal of Computational Acoustics 19, no. 01 (March 2011): 75–93. http://dx.doi.org/10.1142/s0218396x11004316.

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This paper applies a parallel algorithm for a coupled Finite Element/Scaled Boundary Element (FEM/SBFEM)-approach to study soil-structure-interaction problems. The application code is designed to run on clusters of computers, and it enables the analysis of large-scale problems. A crucial point of the approach is that the SBFEM fulfills the radiation condition. Hence, the hybrid numerical approach is well suited for such problems where wave propagation to infinity in an unbounded domain must be considered. The main focus of the paper is to show the applicability of the numerical implementation on large scale problems. First the coupled FEM/SBFEM approach is validated by comparing the numerical results with a semi-analytical solution for a settlement problem. Then the implemented algorithm is applied to study the dynamical behavior of founded wind energy plants under time dependent loading.

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38

Moon, Jucheol, and Oliver Eulenstein. "Synthesizing large-scale species trees using the strict consensus approach." Journal of Bioinformatics and Computational Biology 15, no. 03 (April 20, 2017): 1740002. http://dx.doi.org/10.1142/s0219720017400029.

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Supertree problems are a standard tool for synthesizing large-scale species trees from a given collection of gene trees under some problem-specific objective. Unfortunately, these problems are typically NP-hard, and often remain so when their instances are restricted to rooted gene trees sampled from the same species. While a class of restricted supertree problems has been effectively addressed by the parameterized strict consensus approach, in practice, most gene trees are unrooted and sampled from different species. Here, we overcome this stringent limitation by describing efficient algorithms that are adopting the strict consensus approach to also handle unrestricted supertree problems. Finally, we demonstrate the performance of our algorithms in a comparative study with classic supertree heuristics using simulated and empirical data sets.

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39

Golub, Gene H., and Urs von Matt. "Generalized Cross-Validation for Large-Scale Problems." Journal of Computational and Graphical Statistics 6, no. 1 (March 1997): 1. http://dx.doi.org/10.2307/1390722.

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40

Bischof, Christian H., H. Martin Bücker, Bruno Lang, and Arno Rasch. "Solving large-scale optimization problems with EFCOSS." Advances in Engineering Software 34, no. 10 (October 2003): 633–39. http://dx.doi.org/10.1016/s0965-9978(03)00094-2.

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41

Khokhlov, Nikolay, Nikolay Yavich, Mikhail Malovichko, and Igor Petrov. "Solution of Large-scale Seismic Modeling Problems." Procedia Computer Science 66 (2015): 191–99. http://dx.doi.org/10.1016/j.procs.2015.11.023.

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42

MIYAGI, Akiharu. "Large-scale repair of condominiums and problems." Japanese Journal of Real Estate Sciences 33, no. 1 (June 27, 2019): 63–70. http://dx.doi.org/10.5736/jares.33.1_63.

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43

Lessi, O., and L. Olivi. "Problems of Integration for Large Scale Systems." IFAC Proceedings Volumes 28, no. 23 (September 1995): 59–64. http://dx.doi.org/10.1016/s1474-6670(17)46595-5.

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44

Lavaei, Javad, Aydin Babakhani, Ali Hajimiri, and John C. Doyle. "Solving Large-Scale Hybrid Circuit-Antenna Problems." IEEE Transactions on Circuits and Systems I: Regular Papers 58, no. 2 (February 2011): 374–87. http://dx.doi.org/10.1109/tcsi.2010.2072010.

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45

Abdel-Aziz, Mohammedi R., and Mahmoud M. El-Alem. "Solving large-scale constrained least-squares problems." Applied Mathematics and Computation 137, no. 2-3 (May 2003): 571–87. http://dx.doi.org/10.1016/s0096-3003(02)00161-3.

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46

Keyes, David E., Daniel R. Reynolds, and Carol S. Woodward. "Implicit solvers for large-scale nonlinear problems." Journal of Physics: Conference Series 46 (September 1, 2006): 433–42. http://dx.doi.org/10.1088/1742-6596/46/1/060.

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47

GILBERT, J. C. "NON-LINEAR OPTIMIZATION AND LARGE-SCALE PROBLEMS." Engineering Optimization 18, no. 1-3 (November 1991): 5–21. http://dx.doi.org/10.1080/03052159108941009.

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48

Koscheyev, Victor S., and Ian A. Greaves. "Public Health Problems After Large-Scale Disasters." Prehospital and Disaster Medicine 11, S1 (June 1996): S9—S10. http://dx.doi.org/10.1017/s1049023x00042497.

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49

Trubowitz, Sidney. "Predictable Problems in Achieving Large-Scale Change." Phi Delta Kappan 82, no. 2 (October 2000): 166–68. http://dx.doi.org/10.1177/003172170008200216.

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50

Golub, Gene H., and Urs von Matt. "Generalized Cross-Validation for Large-Scale Problems." Journal of Computational and Graphical Statistics 6, no. 1 (March 1997): 1–34. http://dx.doi.org/10.1080/10618600.1997.10474725.

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