The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015. The 31 contributions presented were carefully reviewed and selected for inclusion in this book. The papers address all fields between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Special focus is given to algorithm selection and configuration, learning, fitness landscape, applications, dynamic optimization, multi-objective, max-clique problems, bayesian optimization and global optimization, data mining and - in a special session - also on dynamic optimization.