Exact and Heuristic Methods in Combinatorial Optimization

1 Introduction.- 2 Heuristic Methods.- 3 Meta-Heuristics.- 4 Branch-and-Bound.- 5 Branch-and-Cut.- 6 The Linear Ordering Polytope.- 7 Further Aspects.- References.- Index.

Rafael Martí is Professor of Statistics and Operations Research at the University of Valencia, Spain. He received a doctoral degree in Mathematics in 1994, and has done extensive research in metaheuristics for hard optimization problems. Dr Martí has about 200 publications, half of them in indexed journals (JCR). He authored several books in optimization, included the co-edited Handbook of Heuristics, a 3-volume reference in the area, published by Springer (2018). Prof. Martí has supervised 7 doctoral and 14 Master thesis, and has secured an American patent. Prof. Martí is currently area editor in the Journal of Heuristics, and associate editor in several journals, including the European Journal of Operational Research, and Math. Prog. Computation. He is Senior Research Associate of the private company OptTek Systems (USA), and has given more than 50 invited and plenary talks. Dr. Martí has been invited Professor in many universities, including the University of Colorado (USA), the University of Molde (Norway), the University of Wien (Austria), the University of Bretagne-Sud (France), or the University College of Dublin (Ireland). He coordinates the Spanish Network on Metaheuristics, funded by the Spanish government as a Network of excellence, and the doctoral program "Statistics and Optimization" at the Univerity of Valencia.
Gerhard Reinelt is professor of Computer Science at Heidelberg University, Germany, since 1992. He received a doctoral degree in Mathematics in 1985 and habilitated in Computer Science in 1991, both at the University of Augsburg, Germany. His main research activities are concerned with the development, analysis and implementation of algorithms for the solution of large-scale combinatorial optimization and mixed-integer programming problems. This comprises the design of fast approximate heuristics as well as the development of algorithms for computing provably optimum solutions, where emphasis is laid on methods for

"The book is well suited for readers who want to learn how to solve real world combinatorial optimization problems as the methods are well explained and a lot of algorithms are given with pseudo-code. The authors explain all terms they use and the book is well understandable. ... All in all this book can be recommended to anyone interested in combinatorial optimization who wants to get an overview of the classical solution approaches in this field." (Isabel Beckenbach, zbMATH 1500.90001, 2023)