Yohannes, Arega W. · Atlanta University Center Robert W. Woodruff Library (Atlanta University Center Robert W. Woodruff Library) · 1981
The fundamental goal, in preparing this thesis, is two-fold. First, the author shows the systematic development of the basic theory of Dynamic Programming. Secondly, the author demonstrates the applicability of this theory in the actual problem solving of Dynamic Programming.\nA very careful balance has been maintained in the setting of the theory and in its applicability of solving problems. Basic theory has been established and expanded systematically and explained vividly. However, it is short and precise. Nevertheless, it presents the tools to handle highly complex problems in Dynamic Programming. Also, the theory is used to prove a general case of an N-stage optimization which demonstrates the sufficiency and capability of the theory.
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Özkan Ufuk Nalbantoğlu · Methods in molecular biology · 2013
Independent scoring of the aligned sections to determine the quality of biological sequence alignments enables recursive definitions of the overall alignment score. This property is not only biologically meaningful but it also provides the opportunity to find the optimal alignments using dynamic programming-based algorithms. Dynamic programming is an efficient problem solving technique for a class of problems that can be solved by dividing into overlapping subproblems. Pairwise sequence alignment techniques such as Needleman-Wunsch and Smith-Waterman algorithms are applications of dynamic programming on pairwise sequence alignment problems. These algorithms offer polynomial time and space solutions. In this chapter, we introduce the basic dynamic programming solutions for global, semi-global, and local alignment problems. Algorithmic improvements offering quadratic-time and linear-space programs and approximate solutions with space-reduction and seeding heuristics are discussed. We finally introduce the application of these techniques on multiple sequence alignment briefly.
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Agliardi, Elettra · AMS Campus - AlmaDL · 2016
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Hendriks, T.H.B. · Socio-Environmental Systems Modeling · 2007
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Heij, W. · Socio-Environmental Systems Modeling · 1981
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Albert Newhouse, Richard Bellman · American Mathematical Monthly · 1958
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Bruno Escoffier, Olivier Spanjaard · 2013
This chapter contains sections titled: Introduction A first example: crossing the bridge Formalization Some other examples Solution Solution of the examples A few extensions Conclusion Bibliography
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Antti Laaksonen · Undergraduate topics in computer science · 2024
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Jianfeng Ren, Andric Li · 2025
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H. A. Eiselt, C.-L. Sandblom · 2000
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ทศพร แสงจ้า · NRCT Data Center · 2023
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Andrej M. Brandt, Wojciech Dzieniszewski, Stefan Jendo et al. · 1984
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Marko Čepin · 2011
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Gjerrit Meinsma, Arjan van der Schaft · Springer undergraduate texts in mathematics and technology · 2023
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Philip D. Loewen · CRM proceedings & lecture notes · 1993
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Gerald Shively · Classroom companion: economics · 2025
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WORLD SCIENTIFIC eBooks · 2026
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Ashok D. Belegundu, Tirupathi R. Chandrupatla · Cambridge University Press eBooks · 2018
In this revised and enhanced second edition of Optimization Concepts and Applications in Engineering, the already robust pedagogy has been enhanced with more detailed explanations, an increased number of solved examples and end-of-chapter problems. The source codes are now available free on multiple platforms. It is vitally important to meet or exceed previous quality and reliability standards while at the same time reducing resource consumption. This textbook addresses this critical imperative integrating theory, modeling, the development of numerical methods, and problem solving, thus preparing the student to apply optimization to real-world problems. This text covers a broad variety of optimization problems using: unconstrained, constrained, gradient, and non-gradient techniques; duality concepts; multiobjective optimization; linear, integer, geometric, and dynamic programming with applications; and finite element-based optimization. It is ideal for advanced undergraduate or graduate courses and for practising engineers in all engineering disciplines, as well as in applied mathematics.
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Stuart E. Dreyfus · WORLD SCIENTIFIC eBooks · 1987
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William D. Sudderth · Encyclopedia of Statistical Sciences · 2005
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