Different Approaches to Numerical Techniques and Different Ways of Regarding Heuristics: Possibilities and Limitations

  • Jonas Mockus
  • William Eddy
  • Audris Mockus
  • Linas Mockus
  • Gintaras Reklaitis
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 17)

Abstract

The aim of this book is to investigate the advantages and limitations of different approaches and different heuristic techniques of optimization. We proceed from the formal Bayesian Approach (BA) to the semi-formal Bayesian Heuristic Approach (BHA) and finally, to the informal Dynamic Visualization Approach (DVA). Therefore, in addition to BA and BHA algorithms, we discuss various visualization techniques and their application to case studies of optimal decision making.

Keywords

Global Optimization Randomization Parameter Pareto Optimality Batch Schedule Restricted Candidate List 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Jonas Mockus
    • 1
    • 2
    • 3
  • William Eddy
    • 4
  • Audris Mockus
    • 5
  • Linas Mockus
    • 6
  • Gintaras Reklaitis
    • 6
  1. 1.Institute of Mathematics and InformaticsKaunas Technological UniversityVilniusLithuania
  2. 2.Vytautas Magnus UniversityVilniusLithuania
  3. 3.Vilnius Technical UniversityVilniusLithuania
  4. 4.Department of StatisticsCarnegie-Mellon UniversityPittsburghUSA
  5. 5.Lucent Technologies AT&T Bell LaboratoriesPittsburghUSA
  6. 6.School of Chemical EngineeringPurdue UniversityW. LafayetteUSA

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