· Includes many applications to real-world problems such as engineering design and scheduling.
· Provides discussions of advanced topics and future research.
· Contains exercises and solutions to enhance the material.
· Written in way that is accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms.
Foreword.
Preface.
Prologue.
· Multi-Objective Optimization.
· Classical Methods.
· Evolutionary Algorithms.
· Non-Elitist Multi-Objective Evolutionary Algorithms.
· Elitist Multi-Objective Evolutionary Algorithms.
· Constrained Multi-Objective Evolutionary Algorithms.
· Salient Issues of Multi-Objective Evolutionary Algorithms.
· Applications of Multi-Objective Evolutionary Algorithms.
Epilogue.
References.
Index.
· Multi-Objective Optimization.
· Classical Methods.
· Evolutionary Algorithms.
· Non-Elitist Multi-Objective Evolutionary Algorithms.
· Elitist Multi-Objective Evolutionary Algorithms.
· Constrained Multi-Objective Evolutionary Algorithms.
· Salient Issues of Multi-Objective Evolutionary Algorithms.
· Applications of Multi-Objective Evolutionary Algorithms.
