Abstract
Approximation algorithms for the Minimal Cover Problem (MCP) are presented in this paper. Contrary to the greedy approximation algorithm for MCP [Jo-74], [Lo-75], [Co-92], novel approaches to MCP are based on the simulated annealing (SA) and genetic algorithms (GA). The main difference between the existing technique and the new method is that the former algorithm gives one solution whereas the latter algorithms improves simultaneously several solutions. This property is important, particularly in the context of the problem of dependence relation of attributes in information systems [Pa-82], [Sk-92].
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© 1994 British Computer Society
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Sapiecha, P. (1994). A Novel Approach to the Minimal Cover Problem. In: Ziarko, W.P. (eds) Rough Sets, Fuzzy Sets and Knowledge Discovery. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3238-7_28
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DOI: https://doi.org/10.1007/978-1-4471-3238-7_28
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