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CCE
2006
13 years 8 months ago
An efficient algorithm for large scale stochastic nonlinear programming problems
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
Y. Shastri, Urmila M. Diwekar
CVPR
2007
IEEE
14 years 10 months ago
Solving Large Scale Binary Quadratic Problems: Spectral Methods vs. Semidefinite Programming
In this paper we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of comput...
Carl Olsson, Anders P. Eriksson, Fredrik Kahl
IPPS
2008
IEEE
14 years 3 months ago
A genetic programming approach to solve scheduling problems with parallel simulation
—Scheduling and dispatching are two ways of solving production planning problems. In this work, based on preceding works, it is explained how these two approaches can be combined...
Andreas Beham, Stephan M. Winkler, Stefan Wagner 0...
HEURISTICS
1998
103views more  HEURISTICS 1998»
13 years 8 months ago
Computing Approximate Solutions of the Maximum Covering Problem with GRASP
We consider the maximum covering problem, a combinatorial optimization problem that arises in many facility location problems. In this problem, a potential facility site covers a s...
Mauricio G. C. Resende
LPNMR
2009
Springer
14 years 1 months ago
Computing Weighted Solutions in Answer Set Programming
For some problems with many solutions, like planning and phylogeny reconstruction, one way to compute more desirable solutions is to assign weights to solutions, and then pick the ...
Duygu Çakmak, Esra Erdem, Halit Erdogan