Java Library of Graph Algorithms and Optimization
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A01=Hang T. Lau
Adjacency Matrix
advanced graph algorithms for researchers
algorithmic complexity
args
Augmenting Path
Author_Hang T. Lau
aux1
Basic Feasible Solution
Category=UB
Category=UMB
Category=UMX
Category=UY
Chromatic Polynomial
combinatorial optimisation
computational problem solving
discrete mathematics
Dual Simplex Method
Endnode
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eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
graph colouring techniques
Graph Isomorphism
Hamilton Cycle
Input Graph
Int
Int A
Int Aux1
Integer Programming Problem
Minimum Cut Set
network flow analysis
Nonbasic Variable
Objective Function
parameters
procedure
Procedure Parameters
public
Public Class
Public Static Void
Revised Simplex Method
Shortest Path Distance
Simple Undirected Graph
static
Static Private Void
string
String Args
undirected
Undirected Graph
void
Product details
- ISBN 9781584887188
- Weight: 900g
- Dimensions: 178 x 254mm
- Publication Date: 20 Oct 2006
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph algorithms and other mathematical programming problems. Collecting some of the most popular graph algorithms and optimization procedures, A Java Library of Graph Algorithms and Optimization provides the source code for a library of Java programs that can be used to solve problems in graph theory and combinatorial optimization. Self-contained and largely independent, each topic starts with a problem description and an outline of the solution procedure, followed by its parameter list specification, source code, and a test example that illustrates the usage of the code.
The book begins with a chapter on random graph generation that examines bipartite, regular, connected, Hamilton, and isomorphic graphs as well as spanning, labeled, and unlabeled rooted trees. It then discusses connectivity procedures, followed by a paths and cycles chapter that contains the Chinese postman and traveling salesman problems, Euler and Hamilton cycles, and shortest paths. The author proceeds to describe two test procedures involving planarity and graph isomorphism. Subsequent chapters deal with graph coloring, graph matching, network flow, and packing and covering, including the assignment, bottleneck assignment, quadratic assignment, multiple knapsack, set covering, and set partitioning problems. The final chapters explore linear, integer, and quadratic programming. The appendices provide references that offer further details of the algorithms and include the definitions of many graph theory terms used in the book.
Lau, Hang T.
