Abstract
In this article we analyze the behavior and scalability of the CHC algorithm over a benchmark of instances of the software project scheduling problem. Our goal is to analyze the performance of the CHC algorithm when solving realistic NP-hard combinatorial problems and test whether its previously reported high performance on similar problems also holds on this one. We perform a preliminary study to obtain a suitable configuration of the parameters in the algorithm. After choosing the configuration, we show the results for the problem instances in the benchmark. To give a reference on how CHC performs and scales, its results are compared against those of a GA. We conclude that CHC outperforms GA in large problem instances. Moreover, CHC produces promising results for the software project scheduling problem domain, and could be used by practitioners.
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Matos, J., Alba, E. (2012). Benchmarking CHC on a New Application: The Software Project Scheduling Problem. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32964-7_45
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DOI: https://doi.org/10.1007/978-3-642-32964-7_45
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