RCMARS: Robustification of CMARS with different scenarios under polyhedral uncertainty set

Ozmen A., Weber G. W., BATMAZ İ., Kropat E.

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, cilt.16, sa.12, ss.4780-4787, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 12
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.cnsns.2011.04.001
  • Dergi Adı: COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.4780-4787
  • Anahtar Kelimeler: Regression, Robust optimization, Robustness, Uncertainty
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Our recently developed CMARS is powerful in handling complex and heterogeneous data. We include into CMARS the existence of uncertainty about the scenarios. Indeed, data include noise in both output and input variables. Therefore, solutions of the optimization problem may reveal a remarkable sensitivity to perturbations in the parameters of the problem. The data uncertainty results in uncertain constraints and objective function. To overcome this difficulty, we refine our CMARS algorithm by a robust optimization technique proposed to cope with data uncertainty. In our previous study, we present the new robust CMARS (RCMARS) in theory and method and illustrate it with a numerical example. In this study, we present RCMARS results with different uncertainty scenarios for our numerical example. (C) 2011 Elsevier B.V. All rights reserved.