Artificial intelligence
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Learning Search Control Knowledge: An Explanation-Based Approach
Learning Search Control Knowledge: An Explanation-Based Approach
Chunking in Soar: The Anatomy of a General Learning Mechanism
Machine Learning
Using Genetic Algorithms in Engineering Design Optimization with Non-Linear Constraints
Proceedings of the 5th International Conference on Genetic Algorithms
Gado: a genetic algorithm for continuous design optimization
Gado: a genetic algorithm for continuous design optimization
Learning to set up numerical optimizations of engineering designs
Data mining for design and manufacturing
Soft computing in engineering design - A review
Advanced Engineering Informatics
ASAGA: an adaptive surrogate-assisted genetic algorithm
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Data driven design optimization methodology a dynamic data driven application system
ICCS'03 Proceedings of the 2003 international conference on Computational science
Constrained multi-objective optimization using steady state genetic algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
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In this paper we describe a method for improving genetic-algorithm-based optimization using search control. The idea is to utilize the sequence of points explored during a search to guide further exploration. The proposed method is particularly suitable for continuous spaces with expensive evaluation functions, such as arise in engineering design. Empirical results in several engineering design domains demonstrate that the proposed method can significantly improve the efficiency and reliability of the GA optimizer.