Titlebook: State-Space Search; Algorithms, Complexi Weixiong Zhang Book 1999 Springer-Verlag New York, Inc. 1999 Extension.Notation.Variable.algorithm

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Weixiong Zhangrekt nachvollziehbar.Ideales Begleitbuch für Selbststudium, Das Buch vermittelt die grundlegenden Konzepte und Zusammenhänge objektorientierter Entwurfsmethoden. Im Mittelpunkt stehen dabei die graphischen Beschreibungstechniken der Unified Modeling Language (UML). Neben einer kurzen Einführung in K

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Weixiong Zhangrekt nachvollziehbar.Ideales Begleitbuch für Selbststudium, Das Buch vermittelt die grundlegenden Konzepte und Zusammenhänge objektorientierter Entwurfsmethoden. Im Mittelpunkt stehen dabei die graphischen Beschreibungstechniken der Unified Modeling Language (UML). Neben einer kurzen Einführung in K

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binatorial optimization problems. The two central themes of this book are the average-case complexity of heuristic state-space search algorithms based on branch-and-bound, and their applications to developing new problem-solving methods and algorithms. Heuristic state-space search is one of the fun

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State-Space Search for Problem Solving, countable set of solutions. The size of the solution space of an NP-hard problem is exponential in term of the problem size in the worst case. Even in an average case, a search algorithm typically explores an exponential number of solutions in order to find an optimal one.

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intertwine

Complexity of State-Space Search for Optimal Solutions,ce search algorithm. The main purpose of an average-case analysis is to find the relationship between the average-case complexity and the accuracy of lower-bound cost functions used by a search algorithm.

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State-Space Search for Problem Solving,, typically those in the NP-hard class [35]. The goal of a search is to quickly find an optimal or near-optimal solution from a finite or infinite but countable set of solutions. The size of the solution space of an NP-hard problem is exponential in term of the problem size in the worst case. Even i

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Algorithms for Combinatorial Optimization,h algorithms based on the branch-and-bound paradigm for solving combinatorial optimization problems exactly, i.e., for finding optimal solutions. Specifically, this chapter considers best-first search, depth-first branch-and-bound, and other search algorithms that can be viewed as nontrivial and non