Non-Convex Multi-Objective Optimization

• 1. Definitions and Examples.- 2. Scalarization.- 3. Approximation and Complexity.- 4. A Brief Review of Non-Convex Single-Objective Optimization.- 5. Multi-Objective Branch and Bound.- 6. Worst-Case Optimal Algorithms.- 7. Statistical Models Based Algorithms.- 8. Probabilistic Bounds in Multi-Objective Optimization.- 9. Visualization of a Set of Pareto Optimal Decisions.- 10. Multi-Objective Optimization Aided Visualization of Business Process Diagrams. –References.- Index.

“Readers will definitely enjoy this book, because all surveyed topics are rigorously exposed. Moreover, since the main prerequisites are provided, the book is essentially self-contained and easy to read. The authors have also included many illustrative pictures that ensure a good understanding of technical concepts and results. … this book is an excellent reference for researchers and graduate students in both pure and applied mathematics, as well as other disciplines.” (Nicolae Popovici, Mathematical Reviews, August, 2018)​