书目名称 | Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining |
编辑 | Hassan AbouEisha,Talha Amin,Mikhail Moshkov |
视频video | |
概述 | Presents different dynamic programming applications in the areas of (i) optimization of decision trees, (ii) optimization of decision rules and systems of decision rules, (iii) optimization of element |
丛书名称 | Intelligent Systems Reference Library |
图书封面 |  |
描述 | .Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. Th |
出版日期 | Book 2019 |
关键词 | Dynamic Programming; Pareto Optimal Points; Bi-criteria Optimization Problem; Matrix Chain Multiplicati |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-319-91839-6 |
isbn_softcover | 978-3-030-06309-2 |
isbn_ebook | 978-3-319-91839-6Series ISSN 1868-4394 Series E-ISSN 1868-4408 |
issn_series | 1868-4394 |
copyright | Springer International Publishing AG, part of Springer Nature 2019 |