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» Unsupervised Problem Decomposition Using Genetic Programming
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PPSN
1994
Springer
14 years 3 months ago
An Evolutionary Algorithm for Integer Programming
Abstract. The mutation distribution of evolutionary algorithms usually is oriented at the type of the search space. Typical examples are binomial distributions for binary strings i...
Günter Rudolph
ICTAI
2000
IEEE
14 years 3 months ago
Constrained genetic algorithms and their applications in nonlinear constrained optimization
This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not ne...
Benjamin W. Wah, Yixin Chen
CCE
2004
13 years 11 months ago
Computational studies using a novel simplicial-approximation based algorithm for MINLP optimization
Significant advances have been made in the last two decades for the effective solution of mixed integer non-linear programming (MINLP) problems, mainly by exploiting the special s...
Vishal Goyal, Marianthi G. Ierapetritou
CVPR
2010
IEEE
14 years 7 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
KBSE
1997
IEEE
14 years 3 months ago
Genetic Algorithms for Dynamic Test Data Generation
In software testing, it is often desirable to find test inputs that exercise specific program features. To find these inputs by hand is extremely time-consuming, especially whe...
Christoph C. Michael, Gary McGraw, Michael Schatz,...