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» Real-World Applications of Multiobjective Optimization
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ICTAI
2009
IEEE
13 years 6 months ago
A Confidence-Based Dominance Operator in Evolutionary Algorithms for Noisy Multiobjective Optimization Problems
This paper describes a noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective fu...
Pruet Boonma, Junichi Suzuki
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
14 years 14 days ago
Comparison of multi-objective evolutionary algorithms in optimizing combinations of reinsurance contracts
Our paper concerns optimal combinations of different types of reinsurance contracts. We introduce a novel approach based on the Mean-Variance-Criterion to solve this task. Two sta...
Ingo Oesterreicher, Andreas Mitschele, Frank Schlo...
EMO
2005
Springer
68views Optimization» more  EMO 2005»
14 years 2 months ago
Multi-objective Optimization of Problems with Epistemic Uncertainty
Abstract. Multi-objective evolutionary algorithms (MOEAs) have proven to be a powerful tool for global optimization purposes of deterministic problem functions. Yet, in many real-w...
Philipp Limbourg
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
14 years 3 months ago
SNDL-MOEA: stored non-domination level MOEA
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -M...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke...
GECCO
2004
Springer
104views Optimization» more  GECCO 2004»
14 years 2 months ago
Optimal Operating Conditions for Overhead Crane Maneuvering Using Multi-objective Evolutionary Algorithms
While operating a crane for maximum productivity, the time of operation and the required energy are two important conflicting factors faced by a crane operator. In such a case, tr...
Kalyanmoy Deb, Naveen Kumar Gupta