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Generalized Scalarizing Model GENS in DSS WebOptim

Generalized Scalarizing Model GENS in DSS WebOptim

Leoneed Kirilov, Vassil Guliashki, Krasimira Genova, Mariana Vassileva, Boris Staykov
Copyright: © 2013 |Volume: 5 |Issue: 3 |Pages: 11
ISSN: 1941-6296|EISSN: 1941-630X|EISBN13: 9781466633476|DOI: 10.4018/jdsst.2013070101
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MLA

Kirilov, Leoneed, et al. "Generalized Scalarizing Model GENS in DSS WebOptim." IJDSST vol.5, no.3 2013: pp.1-11. http://doi.org/10.4018/jdsst.2013070101

APA

Kirilov, L., Guliashki, V., Genova, K., Vassileva, M., & Staykov, B. (2013). Generalized Scalarizing Model GENS in DSS WebOptim. International Journal of Decision Support System Technology (IJDSST), 5(3), 1-11. http://doi.org/10.4018/jdsst.2013070101

Chicago

Kirilov, Leoneed, et al. "Generalized Scalarizing Model GENS in DSS WebOptim," International Journal of Decision Support System Technology (IJDSST) 5, no.3: 1-11. http://doi.org/10.4018/jdsst.2013070101

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Abstract

A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. Its basic characteristics are: user-independent, multisolver-admissibility, method-independent, heterogeneity, web-accessibility. Core system module is an original generalized interactive scalarizing method. It incorporates a number of thirteen interactive methods. Most of the known scalarizing approaches (reference point approach, reference direction approach, classification approach etc.) could be used by changing the method’s parameters. The Decision Maker (DM) can choose the most suitable for him/her form for setting his/her preferences: objective weights, aspiration levels, aspiration directions, aspiration intervals. This information could be changed interactively by the DM during the solution process. Depending on the DM’s preferences form the suitable scalarizing method is chosen automatically. In this way the demands on the DM’s knowledge and experience in the optimization methods area are minimized.

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