Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Orgy in the Computer: Multi-Parent Reproduction in Genetic Algorithms
Proceedings of the Third European Conference on Advances in Artificial Life
On the State of Evolutionary Computation
Proceedings of the 5th International Conference on Genetic Algorithms
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There are presently many and seemingly different optimization algorithms, based on unrelated paradigms. Although some nice and important intuitions support those heuristics, there is (to our knowledge) no rigorous and systematic approach on how to relate them. Herein we present a framework to encompass those heuristics, based on the multiset formalism, providing a common working structure and a basis for their comparison. We show how to express some well known heuristics in our framework and we present some results on relations among them.