M Junger

Computational Combinatorial Optimization: Optimal or Provably Near-Optimal Solutions - Lecture Notes in Computer Science M Junger 2001 edition

Marc Notes: Includes bibliographical references and index. Table of Contents: General Mixed Integer Programming: Computational Issues for Branch-and-Cut Algorithms.- Projection and Lifting in Combinatorial Optimization.- Mathematical Programming Models and Formulations for Deterministic Production Planning Problems.- Lagrangian Relaxation.- Branch-and-Cut Algorithms for Combinatorial Optimization and Their Implementation in ABACUS.- Branch, Cut, and Price: Sequential and Parallel.- TSP Cuts Which Do Not Conform to the Template Paradigm. Publisher Marketing: This tutorial contains written versions of seven lectures on computational combinatorial optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modelling are extensively discussed. Applications to prominent combinatorial optimization problems such as production and transport planning, are treated in many places in particular, the book contains an account of the most successful techniques for solving the travelling salesman problem to optimality.