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Combinatorial.Optimization.Algorithms.and.Complexity下载
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2019-09-17 07:30:51
关于模型预测控制简化数据,可以简化模型预测控制算法的计算量。
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Combinatorial.Optimization.Algorithms.and.Complexity下载
关于模型预测控制简化数据,可以简化模型预测控制算法的计算量。 相关下载链接://download.csdn.net/download/conanltc/9104139?utm_source=bbsseo
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Handbook.of.Graph.Theory.
Com
bin
a
tor
ial
.
Optimization
.and.
Algorithm
s.158
The fusion between graph theory and
com
bin
a
tor
ial
optimization
has led to theoretically profound and practically useful
algorithm
s, yet there is no book that currently covers both areas together. Handbook of Graph Theory,
Com
bin
a
tor
ial
Optimization
, and
Algorithm
s is the first to present a unified,
com
prehensive treatment of both graph theory and
com
bin
a
tor
ial
optimization
. Divided into 11 cohesive sections, the handbook’s 44 chapters focus on graph theory,
com
bin
a
tor
ial
optimization
, and
algorithm
ic issues. The book provides readers with the
algorithm
ic and theoretical foundations to: Understand phenomena as shaped by their graph structures Develop needed
algorithm
ic and
optimization
tools for the study of graph structures Design and plan graph structures that lead to certain desirable behavior With contributions from more than 40 worldwide experts, this handbook equips readers with the necessary techniques and tools to solve problems in a variety of applications. Readers gain exposure to the theoretical and
algorithm
ic foundations of a wide range of topics in graph theory and
com
bin
a
tor
ial
optimization
, enabling them to identify (and hence solve) problems encountered in diverse disciplines, such as electrical,
com
munication,
com
puter, soc
ial
, transportation, biological, and other networks. Table of Contents SECTION I - Basic Concepts and
Algorithm
s CHAPTER 1 - Basic Concepts in Graph Theory and
Algorithm
s CHAPTER 2 - Basic Graph
Algorithm
s CHAPTER 3 - Depth-First Search and Applications SECTION II - Flows in Networks CHAPTER 4 - Maximum Flow Problem CHAPTER 5 - Minimum Cost Flow Problem CHAPTER 6 - Multi
com
mod
ity
Flows SECTION III - Algebraic Graph Theory CHAPTER 7 - Graphs and Vec
tor
Spaces CHAPTER 8 - Incidence, Cut, and Circuit Matrices of a Graph CHAPTER 9 - Adjacency Matrix and Signal Flow Graphs CHAPTER 10 - Adjacency Spectrum and the Laplacian Spectrum of a Graph CHAPTER 11 - Resistance Networks, Random Walks, and Network Theorems SECTION IV - Structural Graph Theory CHAPTER 12 - Connectiv
ity
CHAPTER 13 - Connectiv
ity
Algorithm
s CHAPTER 14 - Graph Connectiv
ity
Augmentation CHAPTER 15 - Matchings CHAPTER 16 - Matching
Algorithm
s CHAPTER 17 - Stable Marriage Problem CHAPTER 18 - Domination in Graphs CHAPTER 19 - Graph Colorings SECTION V - Planar Graphs CHAPTER 20 - Planar
ity
and Dual
ity
CHAPTER 21 - Edge Addition Planar
ity
Testing
Algorithm
CHAPTER 22 - Planar
ity
Testing Based on PC-Trees CHAPTER 23 - Graph Drawing SECTION VI - Interconnection Networks CHAPTER 24 - Introduction to Interconnection Networks CHAPTER 25 - Cayley Graphs CHAPTER 26 - Graph Embedding and Interconnection Networks SECTION VII - Spec
ial
Graphs CHAPTER 27 - Program Graphs CHAPTER 28 - Perfect Graphs CHAPTER 29 - Tree-Structured Graphs SECTION VIII - Partitioning CHAPTER 30 - Graph and Hypergraph Partitioning SECTION IX - Matroids CHAPTER 31 - Matroids CHAPTER 32 - Hybrid Analysis and
Com
bin
a
tor
ial
Optimization
SECTION X - Probabilistic Methods, Random Graph Models, and Randomized
Algorithm
s CHAPTER 33 - Probabilistic Arguments in
Com
bin
a
tor
ics CHAPTER 34 - Random Models and Analyses for Chemical Graphs CHAPTER 35 - Randomized Graph
Algorithm
s: Techniques and Analysis SECTION XI - Coping with NP-
Com
pleteness CHAPTER 36 - General Techniques for
Com
bin
a
tor
ial
Approximation CHAPTER 37 - ε-Approximation Schemes for the Constrained Shortest Path Problem CHAPTER 38 - Constrained Shortest Path Problem: Lagrangian Relaxation-Based
Algorithm
ic Approaches CHAPTER 39 -
Algorithm
s for Finding Disjoint Paths with QoS Constraints CHAPTER 40 - Set-Cover Approximation CHAPTER 41 - Approximation Schemes for Fractional Multi
com
mod
ity
Flow Problems CHAPTER 42 - Approximation
Algorithm
s for Connectiv
ity
Problems CHAPTER 43 - Rectilinear Steiner Minimum Trees CHAPTER 44 - Parameter
Algorithm
s and
Com
plex
ity
Com
bin
a
tor
ial
.
Optimization
.
Algorithm
s.and.
Com
plex
ity
关于模型预测控制简化数据,可以简化模型预测控制算法的计算量。
Com
bin
a
tor
ial
optimization
algorithm
s and
Com
plex
ity
(组合最优化算法和复杂性) EN part1.pdf
共3部分,这是part1
Com
bin
a
tor
ial
optimization
algorithm
s and
Com
plex
ity
(组合最优化算法和复杂性) Author: Christos H.Papadimitriou Kenneth Steiglitz
Com
bin
a
tor
ial
optimization
algorithm
s and
Com
plex
ity
(组合最优化算法和复杂性) EN part2.pdf
共3部分,这是part2
Com
bin
a
tor
ial
optimization
algorithm
s and
Com
plex
ity
(组合最优化算法和复杂性) Author: Christos H.Papadimitriou Kenneth Steiglitz
Com
bin
a
tor
ial
optimization
algorithm
s and
Com
plex
ity
(组合最优化算法和复杂性) EN part3.pdf
共3部分,这是part3
Com
bin
a
tor
ial
optimization
algorithm
s and
Com
plex
ity
(组合最优化算法和复杂性) Author: Christos H.Papadimitriou Kenneth Steiglitz
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