925 research outputs found
COMPUTATIONAL EXPERIENCE WITH THE CHOW-YORKE
No full textThe Chow-Yorke algorithm is a nonsimplicial homotopy-type method for computing Brouwer fixed points that is globally convergent. It is efficient and accurate for fixed point problems. L. T. Watson, T. Y. Li, and C. Y. Wang have adapted the method for zero finding problems, the nonlinear complementarity problem, and nonlinear two-point boundary value problems. Here theoretical justification is given for applying the method to some mathematical programming problems, and computational results are presented
Computational Experience with the Chow-yorke
No full textThe Chow-Yorke algorithm is a nonsimplicial homotopy-type method for computing Brouwer fixed points that is globally convergent. It is efficient and accurate for fixed point problems. L. T. Watson, T. Y. Li, and C. Y. Wang have adapted the method for zero finding problems, the nonlinear complementarity problem, and nonlinear two-point boundary value problems. Here theoretical justification is given for applying the method to some mathematical programming problems, and computational results are presented
Probability-One Homotopy Maps for Mixed Complementarity Problems
No full textProbability-one homotopy algorithms have strong convergence characteristics under mild assumptions. Such algorithms for mixed complementarity problems (MCPs) have potentially wide impact because MCPs are pervasive in science and engineering. A probability-one homotopy algorithm for MCPs was developed earlier by Billups and Watson based on the default homotopy mapping. This algorithm had guaranteed global convergence under some mild conditions, and was able to solve most of the MCPs from the MCPLIB test library. This thesis extends that work by presenting some other homotopy mappings, enabling the solution of all the remaining problems from MCPLIB. The homotopy maps employed are the Newton homotopy and homotopy parameter embeddings.Master of Scienc
A Distributed Genetic Algorithm With Migration for the Design of Composite Laminate Structures
No full textThis thesis describes the development of a general Fortran 90 framework for the solution of composite laminate design problems using a genetic algorithm (GA). The initial Fortran 90 module and package of operators result in a standard genetic algorithm (sGA). The sGA is extended to operate on a parallel processor, and a migration algorithm is introduced. These extensions result in the distributed genetic algorithm with migration (dGA).
The performance of the dGA in terms of cost and reliability is studied and compared to an sGA baseline, using two types of composite laminate design problems. The nondeterminism of GAs and the migration and dynamic load balancing algorithm used in this work result in a changed (diminished) workload, so conventional measures of parallelizability are not meaningful. Thus, a set of experiments is devised to characterize the run time performance of the dGA.
The migration algorithm is found to diminish the normalized cost and improve the reliability of a GA optimization run. An effective linear speedup for constant work is achieved, and the dynamic load balancing algorithm with distributed control and token ring termination detection yield improved run time performance.Master of Scienc
A Multi-Core Numerical Framework for Characterizing Flow in Oil Reservoirs
No full textPresented at the SCS Spring Simulation Multi-Conference – SpringSim 2011, April 4-7, 2011 – Boston, USA Awarded Best Paper in the 19th High Performance Computing Symposium and Best Overall Paper at SpringSim 2011.This paper presents a numerical framework that enables scalable, parallel execution of engineering simulations on multi-core, shared memory architectures. Distribution of the simulations is done by selective hash-tabling of the model domain which spatially decomposes it into a number of orthogonal computational tasks. These tasks, the size of which is critical to optimal cache blocking and consequently performance, are then distributed for execution to multiple threads using the previously presented task management algorithm, H-Dispatch. Two numerical methods, smoothed particle hydrodynamics (SPH) and the lattice Boltzmann method (LBM), are discussed in the present work, although the framework is general enough to be used with any explicit time integration scheme. The implementation of both SPH and the LBM within the parallel framework is outlined, and the performance of each is presented in terms of speed-up and efficiency. On the 24-core server used in this research, near linear scalability was achieved for both numerical methods with utilization efficiencies up to 95%. To close, the framework is employed to simulate fluid flow in a porous rock specimen, which is of broad geophysical significance, particularly in enhanced oil recovery
Convergence of Trust Region Augmented Lagrangian Methods Using Variable Fidelity Approximation Data
No full textTo date the primary focus of most constrained approximate optimization strategies is that application of the method should lead to improved designs. Few researchers have focused on the development of constrained approximate optimization strategies that are assured of converging to a Karush-Kuhn-Tucker (KKT) point for the problem. Recent work by the authors based on a trust region model management strategy has shown promise in managing the convergence of constrained approximate optimization in application to a suite of single level optimization test problems. Using a trust-region model management strategy, coupled with an augmented Lagrangian approach for constrained approximate optimization, the authors have shown in application studies that the approximate optimization process converges to a KKT point for the problem. The approximate optimization strategy sequentially builds a cumulative response surface approximation of the augmented Lagrangian which is then optimized subject to a trust region constraint. In this research the authors develop a formal proof of convergence for the response surface approximation based optimization algorithm. Previous application studies were conducted on single level optimization problems for which response surface approximations were developed using conventional statistical response sampling techniques such as central composite design to query a high fidelity model over the design space. In this research the authors extend the scope of application studies to include the class of multidisciplinary design optimization (MDO) test problems. More importantly the authors show that response surface approximations constructed from variable fidelity data generated during concurrent subspace optimizations (CSSOs) can be effectively managed by the trust region model management strategy. Results for two multidisciplinary test problems are presented in which convergence to a KKT point is observed. The formal proof of convergence and the successfull MDO application of the algorithm using variable fidelity data generated by CSSO are original contributions to the growing body of research in MDO
T-government for benefit realisation
No full textThis paper proposes a model for t-Government and highlights the research agenda needed to
increase understanding of transformational government and the processes involved in
furthering the agenda of the t-Government. In particular, both an operational and a conceptual
model for the effective involvement of citizens and businesses in government functioning
have been proposed. This will help to define an agenda for t-Government research that
emerges from national UK strategy and policy for e-Government. The main threads of t-
Government encompass: (1) A citizen-centric delivery of public services or e-inclusion, (2) A
shared services culture to maximize value added to clients, (3) The effective delivery and
management of resources and skills within government or professionalism. All three threads
should be addressed principally from the perspectives of delivery, evaluation and participation
in view of benefit realisation as envisioned by Government strategic planning and policy
directives (CabinetOffice, 2005). The management of change dimension of these phenomena
have been included in the research agenda. In particular, research is needed to reshape the
discourse towards emphasising a citizen centric approach that defines, develops, and benefits
from public service. Decision makers in Government will need models of Governance that
fulfil transformational objectives. They will also need models of benefits realisation within a
strategic Governance framework. It has been argued that t-Government research should be
addressing these relative voids
Trust region augmented lagrangian methods for sequential response surface approximation and optimization
No full textA common engineering practice is the use of approximation models in place of expensive computer simulations to drive amultidisciplinary design process based on nonlinear programming techniques. The use of approximation strategies is designed to reduce the number of detailed, costly computer simulations required during optimization while maintaining the pertinent features of the design problem. To date the primary focus of most approximate optimization strategies is that application of the method should lead to improved designs. This is a laudable attribute and certainly relevant for practicing designers. However to date few researchers have focused on the development of approximate optimization strategies that are assured of converging to a solution of the original problem. Recent works based on trust region model management strategies have shown promise in managing convergence in unconstrained approximate minimization. In this research we extend these well established notions from the literature on trust-region methods to manage the convergence of the more general approximate optimization problem where equality, inequality and variable bound constraints are present.The primary concern addressed in this study is how to manage the interaction between the optimization and the delity of the approximation models to ensure that the process converges to a solution of the original constrained design problem. Using a trust-region model management strategy, coupled with an augmented Lagrangian approach for constrained approximate optimization, one can show that the optimization process converges to a solution of the original problem. In this research an approx
Globally convergent homotopy methods : a tutorial
No full texthttp://deepblue.lib.umich.edu/bitstream/2027.42/8202/5/bam6921.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/8202/4/bam6921.0001.001.tx
An Experiment Management Component for the WBCSim Problem Solving Environment
No full textThis thesis describes a computing environment WBCSim and its experiment management component. WBCSim is a web-based simulation system used to increase the productivity of wood scientists conducting research on wood-based composite and material manufacturing processes. This experiment management component integrates a web-based graphical front end, server scripts, and a database management system to allow scientists to easily save, retrieve, and perform customized operations on experimental data. A detailed description of the system architecture and the experiment management component is presented, along with a typical scenario of usage.Master of Scienc
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