Progress In Combinatorial Optimization

Progress in Combinatorial Optimization

Metaheuristics

The aim of Metaheuristics: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field. Highlighted are recent developments in the areas of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable Neighborhood Search, Hyper-heuristics, Constraint Programming, Iterated Local Search, GRASP, bio-inspired algorithms like Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization or Swarm Intelligence, and several other paradigms.

Progress in Combinatorial Optimization

This book presents recent developments and new trends in Combinatorial Optimization. Combinatorial Optimization is an active research area that has applications in many domains such as communications, network design, VLSI, scheduling, production, computational biology. In the past years, new results and major advances have been seen in many areas including computational complexity, approximation algorithms, cutting-plane based methods and submodularity function minimization. More efficient and powerful methods have been developed for approaching real-worlds problems, and new concepts and theoritical results have been introduced.