Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis: version 6.13 …

BM Adams, WJ Bohnhoff, KR Dalbey, MS Ebeida… - 2020 - osti.gov
The Dakota toolkit provides a flexible and extensible interface between simulation codes
and iterative analysis methods. Dakota contains algorithms for optimization with gradient …

Sensor placement in municipal water networks

JW Berry, L Fleischer, WE Hart, CA Phillips… - Journal of Water …, 2005 - ascelibrary.org
We present a model for optimizing the placement of sensors in municipal water networks to
detect maliciously injected contaminants. An optimal sensor configuration minimizes the …

DAKOTA: a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0 …

MS Eldred, KR Dalbey, WJ Bohnhoff, BM Adams… - 2010 - osti.gov
The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit
provides a flexible and extensible interface between simulation codes and iterative analysis …

Generalized field-development optimization with derivative-free procedures

OJ Isebor, DE Ciaurri, LJ Durlofsky - Spe Journal, 2014 - onepetro.org
The optimization of general oilfield development problems is considered. Techniques are
presented to simultaneously determine the optimal number and type of new wells, the …

MALLBA: A library of skeletons for combinatorial optimisation

E Alba, F Almeida, M Blesa, J Cabeza, C Cotta… - … Conference on Parallel …, 2002 - Springer
The mallba project tackles the resolution of combinatorial optimization problems using
algorithmic skeletons implemented in C++. mallba offers three families of generic resolution …

Solution of a min-max vehicle routing problem

D Applegate, W Cook, S Dash… - INFORMS Journal on …, 2002 - pubsonline.informs.org
We use a branch-and-cut search to solve the Whizzkids' 96 vehicle routing problem,
demonstrating that the winning solution in the 1996 competition is in fact optimal. Our …

Parallel Branch‐and‐Bound Algorithms

TG Crainic, B Le Cun… - Parallel combinatorial …, 2006 - Wiley Online Library
In the beginning of the twenty-first century, large unsolved combinatorial optimization
problems have been solved exactly. Two impressive cases should be mentioned. First are …

MALLBA: a software library to design efficient optimisation algorithms

E Alba, G Luque, J Garcia-Nieto… - International …, 2007 - inderscienceonline.com
In this paper we discuss on the MALLBA framework, a software tool for the resolution of
combinatorial optimisation problems using generic algorithmic skeletons implemented in …

Parallel branch and cut for capacitated vehicle routing

TK Ralphs - Parallel Computing, 2003 - Elsevier
Combinatorial optimization problems arise commonly in logistics applications. The most
successful approaches to date for solving such problems involve modeling them as integer …

Hedging uncertainty: Approximation algorithms for stochastic optimization problems

R Ravi, A Sinha - International Conference on Integer Programming and …, 2004 - Springer
We study the design of approximation algorithms for stochastic combinatorial optimization
problems. We formulate the problems in the framework of two-stage stochastic optimization …