Abstract
Modern Constraint Logic Programming (CLP) systems have a number of approved features like their declarative programming language, the incorporation of sophisticated search space pruning and propagation algorithms as well as deterministic complete search algorithms. But for very complex, large-scale combinatorial optimization problems as they occur in the real world, CLP often fails to deliver high quality solutions. This is the application area where metaheuristics are often reported to reach dominant results. Consequently, considerable effort has been directed to combine the constraint programming and metaheuristic search paradigms and exploit their respective superior features.
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© 2003 Springer-Verlag Berlin Heidelberg
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Boysen, O. (2003). Extending CLP with Metaheuristics. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_92
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DOI: https://doi.org/10.1007/978-3-540-45193-8_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20202-8
Online ISBN: 978-3-540-45193-8
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