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A First Course in Combinatorial Optimization is a 2004 text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. It is a self-contained treatment of the subject, requiring only some mathematical maturity. Topics include: linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Central to the exposition is the polyhedral viewpoint, which is the key principle underlying the successful integer-programming approach to combinatorial-optimization problems. Another key unifying topic is matroids. The author does not dwell on data structures and implementation details, preferring to focus on the key mathematical ideas that lead to useful models and algorithms. Problems and exercises are included throughout as well as references for further study.

Combinatorial optimization --- Combinatorial optimization. --- Combinatorial analysis. --- Combinatorics --- Algebra --- Mathematical analysis --- Optimization, Combinatorial --- Combinatorial analysis --- Mathematical optimization

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Combinatorial and global optimization problems appear in a wide range of applications in operations research, engineering, biological science, and computer science. In combinatorial optimization and graph theory, many approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic, and algebraic techniques. Such techniques include global optimization formulations, semidefinite programming, and spectral theory. Recent major successes based on these approaches include interior point algorithms for linear and discrete problems, the celebrated

Combinatorial optimization --- Mathematical optimization --- Nonlinear programming --- Programming (Mathematics)

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Computer science --- Combinatorial optimization --- Computer Science --- Informatique --- Optimisation combinatoire

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This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.

Combinatorial optimization. --- Evolutionary computation. --- Computation, Evolutionary --- Neural networks (Computer science) --- Optimization, Combinatorial --- Combinatorial analysis --- Mathematical optimization --- Combinatorial optimization --- Evolutionary computation

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A collection of papers surveying recent progress in the field of Combinatorial Optimization.Topics examined include theoretical and computational aspects (Boolean Programming, Probabilistic Analysis of Algorithms, Parallel Computer Models and Combinatorial Algorithms), well-known combinatorial problems (such as the Linear Assignment Problem, the Quadratic Assignment Problem, the Knapsack Problem and Steiner Problems in Graphs) and more applied problems (such as Network Synthesis and Dynamic Network Optimization, Single Facility Location Problems on Networks, the Vehicle Routing Problem

Combinatorial optimization. --- Combinatorial analysis. --- Combinatorics --- Algebra --- Mathematical analysis --- Optimization, Combinatorial --- Combinatorial analysis --- Mathematical optimization --- Combinatorial optimization --- Optimisation combinatoire --- ELSEVIER-B EPUB-LIV-FT