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CCE
2010
13 years 5 months ago
A simple heuristic for reducing the number of scenarios in two-stage stochastic programming
In this work we address the problem of solving multiscenario optimization models that are deterministic equivalents of two-stage stochastic programs. We present a heuristic approx...
Ramkumar Karuppiah, Mariano Martín, Ignacio...
GECCO
2004
Springer
14 years 1 months ago
Dynamic Uniform Scaling for Multiobjective Genetic Algorithms
Before Multiobjective EvolutionaryAlgorithms (MOEAs) can be used as a widespread tool for solving arbitrary real world problems there are some salient issues which require further ...
Gerulf K. M. Pedersen, David E. Goldberg
EMO
2001
Springer
109views Optimization» more  EMO 2001»
14 years 8 days ago
Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms
When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropri...
Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen
SIAMJO
2008
57views more  SIAMJO 2008»
13 years 7 months ago
Universal Confidence Sets for Solutions of Optimization Problems
We consider random approximations to deterministic optimization problems. The objective function and the constraint set can be approximated simultaneously. Relying on concentratio...
Silvia Vogel
WECWIS
2002
IEEE
130views ECommerce» more  WECWIS 2002»
14 years 20 days ago
A New Category of Business Negotiation Primitives for Bilateral Negotiation Agents and Associated Algorithm to Find Pareto Optim
How to conduct automated business negotiation over the Internet is an important issue for agent research. In most bilateral negotiation models, two negotiation agents negotiate by...
Haifei Li