Abstract
This paper addresses the solution of weighted set covering problems using cultural algorithms. The weighted set covering problem is a reasonably well known NP-complete optimization problem with many real world applications. We use a cultural evolutionary architecture to maintain knowledge of diversity and fitness learned over each generation during the search process. The proposed approach is validated using benchmark instances, and its results are compared with respect to other approaches which have been previously adopted to solve the problem. Our results indicate that the approach is able to produce very competitive results in compare with other algorithms solving the portfolio of test problems taken from the ORLIB.
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Crawford, B., Soto, R., Monfroy, E. (2013). Cultural Algorithms for the Set Covering Problem. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_4
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DOI: https://doi.org/10.1007/978-3-642-38715-9_4
Publisher Name: Springer, Berlin, Heidelberg
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