Extensions of dynamic programming for combinatorial optimization and data mining

0Citations
Citations of this article
21Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In contrast with conventional dynamic programming algorithms that return one solution, extensions of dynamic programming allows us to work with the whole set of solutions or its essential part, to perform multi-stage optimization relative to different criteria, to count the number of solutions, and to find the set of Pareto optimal points for bi-criteria optimization problems. The presentation is based on the results considered in three books published or accepted by Springer.

Cite

CITATION STYLE

APA

Moshkov, M. (2021). Extensions of dynamic programming for combinatorial optimization and data mining. In IFIP Advances in Information and Communication Technology (Vol. 623, pp. 315–316). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-74826-5

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free