Optimization in Engineering Sciences: Metaheuristic, Stochastic Methods and Decision Support [Hardcover]

The purpose of this book is to present the main metaheuristics and approximate and stochastic methods for optimization of complex systems in Engineering Sciences. It has been written within the framework of the European Union project ERRIC (Empowering Romanian Research on Intelligent Information Technologies), which is funded by the EUs FP7 Research Potential program and has been developed in co-operation between French and Romanian teaching researchers. Through the principles of various proposed algorithms (with additional references) this book allows the reader to explore various methods of implementation such as metaheuristics, local search and populationbased methods. It examines multi-objective and stochastic optimization, as well as methods and tools for computer-aided decision-making and simulation for decision-making.

LIST OF FIGURES ix

LIST OF TABLES xiii

LIST OF ALGORITHMS xv

LIST OF ACRONYMS xvii

PREFACE xix

ACKNOWLEDGEMENTS xxi

CHAPTER 1. METAHEURISTICS  LOCAL METHODS 1

1.1. Overview 1

1.2. Monte Carlo principle 6

1.3. Hill climbing 12

1.4. Taboo search 20

1.4.1. Principle 20

1.4.2. Greedy descent algorithm 20

1.4.3. Taboo search method 23

1.4.4. Taboo list 25

1.4.5. Taboo search algorithm 26

1.4.6. Intensification and diversification 30

1.4.7. Application examples 31

1.5. Simulated annealing 39

1.5.1. Principle of thermal annealing 39

1.5.2. Kirkpatricks model of thermal annealing 41

1.5.3. Simulated annealing algorithm 43

1.6. Tunneling 46

1.6.1. Tunneling principle 46