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CEC
2011
IEEE
12 years 4 months ago
Differential evolution with multiple strategies for solving CEC2011 real-world numerical optimization problems
—Over the last two decades, many Differential Evolution (DE) strategies have been introduced for solving Optimization Problems. Due to the variability of the characteristics in o...
Saber M. Elsayed, Ruhul A. Sarker, Daryl Essam
ISDA
2010
IEEE
13 years 2 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
CEC
2009
IEEE
13 years 11 months ago
Multi-objective optimization using self-adaptive differential evolution algorithm
- In this paper, we propose a Multiobjective Self-adaptive Differential Evolution algorithm with objective-wise learning strategies (OW-MOSaDE) to solve numerical optimization pr...
Vicky Ling Huang, Shuguang Z. Zhao, Rammohan Malli...
SEMCCO
2010
13 years 2 months ago
Differential Evolution Algorithm with Ensemble of Parameters and Mutation and Crossover Strategies
Differential Evolution (DE) has attracted much attention recently as an effective approach for solving numerical optimization problems. However, the performance of DE is sensitive ...
Rammohan Mallipeddi, Ponnuthurai Nagaratnam Sugant...
GECCO
2010
Springer
197views Optimization» more  GECCO 2010»
13 years 9 months ago
Adaptive strategy selection in differential evolution
Differential evolution (DE) is a simple yet powerful evolutionary algorithm for global numerical optimization. Different strategies have been proposed for the offspring generation...
Wenyin Gong, Álvaro Fialho, Zhihua Cai