With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computation techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, derived from biologically inspired concepts and are suitable for solving scheduling problems because they are highly scalable and flexible in terms of constraint handling and dual purpose. This edited book provides an overview of many recent developments in the field of scheduling a large and growing evolution, and demonstrates the application of evolutionary computing techniques to solve scheduling problems, not only for small-scale test problems, but also a complete real-world problems.