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GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
14 years 1 months ago
A multi-objective genetic algorithm for robust design optimization
Real-world multi-objective engineering design optimization problems often have parameters with uncontrollable variations. The aim of solving such problems is to obtain solutions t...
Mian Li, Shapour Azarm, Vikrant Aute
GECCO
2007
Springer
154views Optimization» more  GECCO 2007»
14 years 1 months ago
A multi-objective approach to search-based test data generation
There has been a considerable body of work on search–based test data generation for branch coverage. However, hitherto, there has been no work on multi–objective branch covera...
Kiran Lakhotia, Mark Harman, Phil McMinn
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
14 years 1 months ago
Methodology to select solutions from the pareto-optimal set: a comparative study
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
José C. Ferreira, Carlos M. Fonseca, Ant&oa...
GECCO
2010
Springer
217views Optimization» more  GECCO 2010»
13 years 9 months ago
Benchmarking CMA-EGS on the BBOB 2010 noiseless function testbed
This paper describes the implementation and the results for CMA-EGS on the BBOB 2010 noiseless function testbed. The CMA-EGS is a hybrid strategy which combines elements from grad...
Steffen Finck, Hans-Georg Beyer
IEEEARES
2010
IEEE
13 years 11 months ago
Optimising IDS Sensor Placement
—In large network environments multiple intrusion detection sensors are needed to adequately monitor network traffic. However, deploying and managing additional sensors on a lar...
Hao Chen, John A. Clark, Siraj A. Shaikh, Howard C...