Graphs, Algorithms and Optimization
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Table of contents:Graphs and Their Complements. Paths and Walks. Some Special Classes of Graphs. Trees and Cycles. The Structure of Trees. Connectivity. Matchings. Network Flows. Hamilton Cycles. Digraphs. Planarity. Graph Colorings. Graph Embeddings. Discrete Optimization. NP-Completeness.A valuable resource for mathematics and computer science students and professionals, Graphs, Algorithms and Optimization presents the theory of graphs from an algorithmic point of view. The authors cover the key topics in graph theory and introduce discrete optimization and its connection to graph theory. Th...
Table of contents:
Graphs and Their Complements. Paths and Walks. Some Special Classes of Graphs. Trees and Cycles. The Structure of Trees. Connectivity. Matchings. Network Flows. Hamilton Cycles. Digraphs. Planarity. Graph Colorings. Graph Embeddings. Discrete Optimization. NP-Completeness.
A valuable resource for mathematics and computer science students and professionals, Graphs, Algorithms and Optimization presents the theory of graphs from an algorithmic point of view. The authors cover the key topics in graph theory and introduce discrete optimization and its connection to graph theory. The book contains a wealth of information on algorithms and the data structures needed to program them efficiently. Many programming techniques used for algorithms, discussions on algorithmic complexity and efficiency, a chapter on NP-completeness, and three chapters on linear optimization are also included. The graph theory presented is rigorous, but the style is informal.
A valuable resource for mathematics and computer science students, Graphs, Algorithms and Optimization presents the theory of graphs from an algorithmic viewpoint.
Graphs and Their Complements. Paths and Walks. Some Special Classes of Graphs. Trees and Cycles. The Structure of Trees. Connectivity. Matchings. Network Flows. Hamilton Cycles. Digraphs. Planarity. Graph Colorings. Graph Embeddings. Discrete Optimization. NP-Completeness.
A valuable resource for mathematics and computer science students and professionals, Graphs, Algorithms and Optimization presents the theory of graphs from an algorithmic point of view. The authors cover the key topics in graph theory and introduce discrete optimization and its connection to graph theory. The book contains a wealth of information on algorithms and the data structures needed to program them efficiently. Many programming techniques used for algorithms, discussions on algorithmic complexity and efficiency, a chapter on NP-completeness, and three chapters on linear optimization are also included. The graph theory presented is rigorous, but the style is informal.
A valuable resource for mathematics and computer science students, Graphs, Algorithms and Optimization presents the theory of graphs from an algorithmic viewpoint.