Multi-objective optimization with convex quadratic cost functions: A multi-parametric programming approach

•Formulation of the multi-objective optimization problem as a multi-parametric QCQP.•Derivation of suitable affine overestimators with a guaranteed bound of suboptimality.•Solution of the resulting mp-QP problem with state-of-the-art solvers, thus obtaining the Pareto front explicitly.•Numerical exa...

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Veröffentlicht in:Computers & chemical engineering Jg. 85; S. 36 - 39
Hauptverfasser: Oberdieck, Richard, Pistikopoulos, Efstratios N.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 02.02.2016
Schlagworte:
Algorithms
Approximation
Chemical engineering
Cost function
Explicit Pareto front calculation
Mathematical analysis
Multi-objective optimization
Multi-parametric programming
Optimization
Pareto optimality
Programming
Explicit Pareto front calculation
Multi-parametric programming
Multi-objective optimization
ISSN:0098-1354, 1873-4375
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Zusammenfassung:•Formulation of the multi-objective optimization problem as a multi-parametric QCQP.•Derivation of suitable affine overestimators with a guaranteed bound of suboptimality.•Solution of the resulting mp-QP problem with state-of-the-art solvers, thus obtaining the Pareto front explicitly.•Numerical examples highlight the capabilities of this approach. In this note we present an approximate algorithm for the explicit calculation of the Pareto front for multi-objective optimization problems featuring convex quadratic cost functions and linear constraints based on multi-parametric programming and employing a set of suitable overestimators with tunable suboptimality. A numerical example as well as a small computational study highlight the features of the novel algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2015.10.011