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Dynamic Objectives Aggregation in Multi-objective Evolutionary Optimization


  • Gabriella Dellino
  • Mariagrazia Fedele


  • Carlo Meloni


Several approaches for solving multi-objective optimization problems entail a form of scalarization of the objectives. This paper proposes a study of different dynamic objectives aggregation methods in the context of evolutionary algorithms. These methods are mainly based on both weighted sum aggregations and curvature variations. A comparison analysis is presented on the basis of a campaign of computational experiments on a set of benchmark problems from the literature.

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  • Gabriella Dellino & Mariagrazia Fedele & Carlo Meloni, 2008. "Dynamic Objectives Aggregation in Multi-objective Evolutionary Optimization," Quaderni DSEMS 06-2008, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
  • Handle: RePEc:ufg:qdsems:06-2008

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    References listed on IDEAS

    1. Carr, Peter P, 1988. " The Valuation of Sequential Exchange Opportunities," Journal of Finance, American Finance Association, vol. 43(5), pages 1235-1256, December.
    2. Armada, Manuel Rocha & Kryzanowski, Lawrence & Pereira, Paulo Jorge, 2007. "A modified finite-lived American exchange option methodology applied to real options valuation," Global Finance Journal, Elsevier, vol. 17(3), pages 419-438, March.
    3. Geske, Robert & Johnson, Herb E, 1984. " The American Put Option Valued Analytically," Journal of Finance, American Finance Association, vol. 39(5), pages 1511-1524, December.
    4. Barraquand, Jérôme & Martineau, Didier, 1995. "Numerical Valuation of High Dimensional Multivariate American Securities," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(03), pages 383-405, September.
    5. Broadie, Mark & Glasserman, Paul, 1997. "Pricing American-style securities using simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1323-1352, June.
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    Multi-objective optimization; Evolutionary algorithms; Aggregate objective functions;

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