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FSTTCS
2006
Springer
15 years 1 months ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys
94
Voted
CCE
2004
14 years 9 months ago
Dynamic programming in a heuristically confined state space: a stochastic resource-constrained project scheduling application
The Resource-Constrained Project Scheduling Problem(RCPSP) is a significant challenge in highly regulated industries, such as pharmaceuticals and agrochemicals, where a large numb...
Jaein Choi, Matthew J. Realff, Jay H. Lee
IJAR
2008
116views more  IJAR 2008»
14 years 9 months ago
Portfolio management under epistemic uncertainty using stochastic dominance and information-gap theory
Portfolio management in finance is more than a mathematical problem of optimizing performance under risk constraints. A critical factor in practical portfolio problems is severe u...
Daniel Berleant, L. Andrieu, Jean-Philippe Argaud,...
AUTOMATICA
2011
14 years 4 months ago
A frequentist approach to mapping under uncertainty
An asynchronous stochastic approximation based (Frequentist) approach is proposed for mapping using noisy mobile sensors under two different scenarios: 1) perfectly known sensor ...
Suman Chakravorty, R. Saha
AAAI
2007
14 years 11 months ago
Stochastic Optimization for Collision Selection in High Energy Physics
Artificial intelligence has begun to play a critical role in basic science research. In high energy physics, AI methods can aid precision measurements that elucidate the underlyi...
Shimon Whiteson, Daniel Whiteson