Abstract
This paper investigates the adaptive selection of operators in the context of Local Search. The utility of each operator is computed from the solution quality and distance of the candidate solution from the search trajectory. A number of utility measures based on the Pareto dominance relationship and the relative distances between the operators are proposed and evaluated on QAP instances using an implied or static target balance between exploitation and exploration. A refined algorithm with an adaptive target balance is then examined.
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Veerapen, N., Maturana, J., Saubion, F. (2012). A Comparison of Operator Utility Measures for On-Line Operator Selection in Local Search. In: Hamadi, Y., Schoenauer, M. (eds) Learning and Intelligent Optimization. LION 2012. Lecture Notes in Computer Science, vol 7219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_51
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DOI: https://doi.org/10.1007/978-3-642-34413-8_51
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-34413-8
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