Solving Nonconvex Process Optimisation Problems Using Interval Subdivision Algorithms

  • R. P. Byrne
  • I. D. L. Bogle
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 9)


Many Engineering Design problems are nonconvex. A particular approach to global optimisation, the class of ‘Covering Methods’, is reviewed in a general framework. The method can be used to solve general nonconvex problems and provides guarantees that solutions are globally optimal. Aspects of the Interval Subdivision method are presented with the results of their application to some illustrative test problems. The results show the care that must be taken in constructing inclusion functions and demonstrate the effects of some different implementation decisions. Some particular difficulties of applying the method to constrained problems are brought to light by the results.


Feasible Point Interval Analysis Inclusion Function Tight Bound Interval Method 
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 1996

Authors and Affiliations

  • R. P. Byrne
    • 1
  • I. D. L. Bogle
    • 1
  1. 1.Department of Chemical & Biochemical EngineeringUniversity College LondonLondonEngland

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