Handling Constraints in Global Optimization Using Artificial Immune Systems: A Survey
作者： Nareli Cruz-Cortés
DOI: 10.1007/978-3-642-00619-7_11
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摘要: Artificial Immune Systems (AIS) are computational intelligent systems inspired by some processes or theories observed in the biological immune system. They have been applied to solve a wide range of machine learning and optimization problems. In this chapter main AIS-based proposals for solving constrained numerical problems shown. Although first works were hybrid solutions partially based on Genetic Algorithms, most recent algorithms completely features.We show that these represent viable alternatives penalty functions other similar mechanisms handle constraints
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