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MP
2002
110views more  MP 2002»
13 years 5 months ago
Robust optimization - methodology and applications
Abstract. Robust Optimization (RO) is a modeling methodology, combined with computational tools, to process optimization problems in which the data are uncertain and is only known ...
Aharon Ben-Tal, Arkadi Nemirovski
PE
2006
Springer
145views Optimization» more  PE 2006»
13 years 5 months ago
Closed form solutions for mapping general distributions to quasi-minimal PH distributions
Approximating general distributions by phase-type (PH) distributions is a popular technique in stochastic analysis, since the Markovian property of PH distributions often allows a...
Takayuki Osogami, Mor Harchol-Balter
ICML
2009
IEEE
14 years 6 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
IPCO
2004
107views Optimization» more  IPCO 2004»
13 years 7 months ago
A Robust Optimization Approach to Supply Chain Management
Abstract. We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time...
Dimitris Bertsimas, Aurélie Thiele
WSC
2008
13 years 8 months ago
Speeding up call center simulation and optimization by Markov chain uniformization
Staffing and scheduling optimization in large multiskill call centers is time-consuming, mainly because it requires lengthy simulations to evaluate performance measures and their ...
Eric Buist, Wyean Chan, Pierre L'Ecuyer