Solving Nonconvex Process Optimisation Problems Using Interval Subdivision Algorithms
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.
KeywordsFeasible Point Interval Analysis Inclusion Function Tight Bound Interval Method
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