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A decomposition-based crash-start for stochastic programming

Marco Colombo, Andreas Grothey
2013 Computational optimization and applications  
In this paper we propose a crash-start technique for interior point methods applicable to multi-stage stochastic programming problems.  ...  of the solutions of the subproblems as a warm-starting point for the complete instance.  ...  Acknowledgements We would like to thank the two anonymous referees for their helpful comments which have improved the quality of the manuscript.  ... 
doi:10.1007/s10589-012-9530-7 fatcat:miozkyodtjbthdb2r5k2icuxca

Optimization analysis for design and planning of multi-project programs

Victor D. Wiley, Richard F. Deckro, Jack A. Jackson
1998 European Journal of Operational Research  
Decomposition technique to "jump-start" a linear solver was presented.  ...  Stochastic programming approaches may be considered.  ...  Instructions for filling in each block of the form follow. It is important to stay within the lines to meet optical scanning requirements. Block 20. Limitation of Abstract.  ... 
doi:10.1016/s0377-2217(97)00334-2 fatcat:7tontb4o4ffzrorawt6hzsx2q4

Financial Optimization: optimization paradigms and financial planning under uncertainty

Giorgio Consigli, Paolo Brandimarte, Daniel Kuhn
2015 OR spectrum  
stochastic programs, and a stochastic dual dynamic programming approach is proposed for their solution, exploiting the properties of coherent or polyhedral risk measures, as well as a decomposition into  ...  -Article Dupacova and Kozmik (2015) has a strong dynamic stochastic programming flavor, while article Konicz et al. (2015) combines a stochastic programming with a stochastic control modeling framework  ... 
doi:10.1007/s00291-015-0406-y fatcat:kmxcpwshqjfd5mmnypqvtwmewy

Dynamic Stochastic Programming For Asset-liability Management

Giorgio Consigli, M.A.H. Dempster
1998 Social Science Research Network  
Multistage stochastic programming in contrast to stochastic control has found wide application in the formulation and solution of nancial problems characterized by a large number of state variables and  ...  for either linear or quadratic objective, the predictor corrector interior point method provided in OB1, the simplex method of OSL, the MSLiP-OSL code instantiating nested Benders decomposition with subproblem  ...  Acknowledgements The research reported here represents one output of a long term research project conducted by the Finance Research Group, rst at Dalhousie University, subsequently at the University of  ... 
doi:10.2139/ssrn.34780 fatcat:wwug5kekxffhpljh4ilzfrcskq

The stochastic time–cost tradeoff problem: A robust optimization approach

Izack Cohen, Boaz Golany, Avraham Shtub
2007 Networks  
In particular, we show how to implement a state-of-the-art methodology known as "robust optimization" to solve the problem.  ...  We consider the problem of allocating resources to projects performed under given due dates and stochastic time-cost tradeoff settings.  ...  Of course, the responsibility for any errors found in the article rests solely with the authors.  ... 
doi:10.1002/net.20153 fatcat:j676miuejbew3kaesuyaxg5zia

COAP 2013 Best Paper Prize

2014 Computational optimization and applications  
The paper describes the development and implementation of techniques for solving very large scale stochastic linear programming (LP) problems using the dual revised simplex method on large multiprocessor  ...  simplex for large-scale stochastic LP problems" published in volume 55 pages 571-596.  ...  , for example, within a branch-andbound algorithm for solving mixed-integer stochastic programming problems.  ... 
doi:10.1007/s10589-014-9707-3 fatcat:3u6msleya5e7rmbcsxo75rr7na

Reoptimization With the Primal-Dual Interior Point Method

Jacek Gondzio, Andreas Grothey
2002 SIAM Journal on Optimization  
A practical procedure is then derived for an infeasible path-following method. It is applied in the context of crash start for several large-scale structured linear programs.  ...  For large structured linear programs crash start leads to about 40% reduction of the iterations number and translates into 25% reduction of the solution time.  ...  We are grateful to the anonymous referee for his comments.  ... 
doi:10.1137/s1052623401393141 fatcat:es63titut5emfg3nzvmpgm5yom


Zhigang SHEN, Ashkan HASSANI, Qian SHI
2015 Journal of Civil Engineering and Management  
The authors believe Cobb-Douglas function provides a much-needed piece to modeling the cost functions in the construction time-cost tradeoff problem during the crashing process.  ...  A case study was presented to show how the proposed framework works.  ...  Aghaie and Mokhtari (2009) proposed an ant colony optimization for stochastic crashing problem. They also assume a discrete time cost function problem.  ... 
doi:10.3846/13923730.2014.897966 fatcat:e5joa4otinbwfngj5nc4mcogua

The Effect of Price Discount on Time-Cost Trade-off Problem Using Genetic Algorithm

Hadi Mokhtari, Abdollah Aghaie
2009 Engineering  
Time-cost trade off problem (TCTP), known in the literature as project crashing problem (PCP) and project speeding up problem (PSP) is a part of project management in planning phase.  ...  A large amount of literature has studied this problem under various behavior of cost function. But, in all of them, influence of discount has not been investigated.  ...  This study presents a Stochastic Compression Project (SCOP) heuristic based on decomposition of PERT networks into the serial and parallel subnets.  ... 
doi:10.4236/eng.2009.11005 fatcat:npxp4rxwnjbetddkf3t45tsijy

An Agent-Based Model of the Flash Crash of May 6, 2010, with Policy Implications

Tommi A. Vuorenmaa, Liang Wang
2013 Social Science Research Network  
We describe an agent-based framework that successfully simulates the key aspects of the most famous ‡ash crash in history: the Flash Crash of May 6, 2010.  ...  The model can be used for stress-testing algorithms before their production stage and to give sounder policy advice.  ...  We use this decomposition as a useful basis for our agent-based model, but simplify the classi…cation.  ... 
doi:10.2139/ssrn.2336772 fatcat:62lwcswb6zfafascbi3i2da2zm

EVPI-Based Importance Sampling Solution Procedures for Multistage Stochastic Linear Programmes on Parallel MIMD Architectures

M.A.H. Dempster, R.T. Thompson
1997 Social Science Research Network  
A parallel version of an importance sampling solution algorithm based on local EVPI information has been developed for extremely large multistage stochastic linear programmes which either have too many  ...  Multistage stochastic linear programming has many practical applications for problems whose current decisions have to be made under future uncertainty.  ...  access to and support for the parallel computing facilities used in the experiments reported here.  ... 
doi:10.2139/ssrn.37767 fatcat:ftndimvugfegvfir7ulucgxlci

Resilience in Numerical Methods: A Position on Fault Models and Methodologies [article]

James Elliott and Mark Hoemmen and Frank Mueller
2014 arXiv   pre-print
However, resilience research struggles to come up with useful abstract programming models for reasoning about SDC.  ...  Existing work randomly flips bits in running applications, but this only shows average-case behavior for a low-level, artificial hardware model.  ...  Second, it could crash the process, for example due to a segmentation violation or an invalid instruction.  ... 
arXiv:1401.3013v1 fatcat:jqj3gp44gbcj7ps5ac72hmx3r4

Parallelization and Aggregation of Nested Benders Decomposition

M.A.H. Dempster, R.T. Thompson
1997 Social Science Research Network  
There are a variety of methods for solving these problems, including nested Benders decomposition.  ...  Dynamic multistage stochastic linear programming has many practical applications for problems whose current decisions have to be made under future uncertainty.  ...  A. C.  ... 
doi:10.2139/ssrn.37765 fatcat:t5q5kkfakzb3tnd4a7q5cvykqy

An EEMD Aided Comparison of Time Histories and Its Application in Vehicle Safety

Zuolong Wei, Kjell Gunnar Robbersmyr, Hamid Reza Karimi
2017 IEEE Access  
More specifically, each signal for comparison is decomposed into a trend signal and several intrinsic mode functions (IMFs) by ensemble empirical mode decomposition.  ...  INDEX TERMS Time-history, model validation, Ensemble Empirical Mode Decomposition (EEMD), dynamic time warping (DTW), vehicle crash.  ...  two crash signals start at the same stage.  ... 
doi:10.1109/access.2016.2644662 fatcat:isdk4tnxazdovdekdikxdbe2la

A Scenario Decomposition Algorithm for Stochastic Programming Problems with a Class of Downside Risk Measures

Maciej Rysz, Alexander Vinel, Pavlo Krokhmal, Eduardo L. Pasiliao
2015 INFORMS journal on computing  
We present an efficient scenario decomposition algorithm for solving large-scale convex stochastic programming problems that involve a particular class of downside risk measures.  ...  It is demonstrated that for large-scale nonlinear problems the proposed approach can provide up to an order of magnitude of improvement in computational time in comparison to state-of-the-art solvers,  ...  In what follows, we develop a general scenario decomposition solution framework for solving stochastic optimization problems with certainty equivalent-based risk measures by utilizing principles related  ... 
doi:10.1287/ijoc.2014.0635 fatcat:fkovqzde7zbrbox7o36v7hdl6q
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