Meta Heuristic Techniques in Software Engineering and Its Applications

This book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains are discussed in this book that help the global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. It also discovers novel ways to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms gives the idea to beginners to apply the common approaches to optimization problem. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract the researchers to apply the hybrid metaheuristics in real scenarios.