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CEC
2007
IEEE
14 years 1 months ago
Improving hypervolume-based multiobjective evolutionary algorithms by using objective reduction methods
— Hypervolume based multiobjective evolutionary algorithms (MOEA) nowadays seem to be the first choice when handling multiobjective optimization problems with many, i.e., at lea...
Dimo Brockhoff, Eckart Zitzler
PPSN
2004
Springer
14 years 21 days ago
Searching Transcriptional Modules Using Evolutionary Algorithms
The mechanism of gene regulation has been studied intensely for decades. It is important to identify synergistic transcriptional motifs. Its search space is so large that an effici...
Je-Gun Joung, Sok June Oh, Byoung-Tak Zhang
EMO
2009
Springer
190views Optimization» more  EMO 2009»
14 years 1 months ago
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in ma...
Kalyanmoy Deb, Ankur Sinha
ISCI
2010
128views more  ISCI 2010»
13 years 5 months ago
Robust static output feedback controller synthesis using Kharitonov's theorem and evolutionary algorithms
This paper presents a simple but effective tuning strategy for robust static output feedback (SOF) controllers with minimal quadratic cost in the context of multiple parametric un...
Rosario Toscano, Patrick Lyonnet
EMO
2001
Springer
107views Optimization» more  EMO 2001»
13 years 12 months ago
Multi-objective Optimisation of Cancer Chemotherapy Using Evolutionary Algorithms
The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, t...
Andrei Petrovski, John A. W. McCall