The Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the numerous applications of approximation algorithms and metaheuristics.
Volume I (Methodologies and Traditional Applications) of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, rounding, transformation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, ant colony optimization, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems.
Volume 2 (Contemporary and Emerging Applications) focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more.
The difference between the covers in the two volumes is meant to represents the applications layer, the main theme of Volume II. Can you spot the place where the pictures were taken?