@article{1432895,
      recid = {1432895},
      author = {Jiang, Chao, and Han, Xu, and Xie, Huichao,},
      title = {Nonlinear interval optimization for uncertain problems /},
      pages = {1 online resource (291 pages)},
      abstract = {This book systematically discusses nonlinear interval  optimization design theory and methods. Firstly, adopting a  mathematical programming theory perspective, it develops an  innovative mathematical transformation model to deal with  general nonlinear interval uncertain optimization problems,  which is able to equivalently convert complex interval  uncertain optimization problems to simple deterministic  optimization problems. This model is then used as the basis  for various interval uncertain optimization algorithms for  engineering applications, which address the low efficiency  caused by double-layer nested optimization. Further, the  book extends the nonlinear interval optimization theory to  design problems associated with multiple optimization  objectives, multiple disciplines, and parameter dependence,  and establishes the corresponding interval optimization  models and solution algorithms. Lastly, it uses the  proposed interval uncertain optimization models and methods  to deal with practical problems in mechanical engineering  and related fields, demonstrating the effectiveness of the  models and methods.},
      url = {http://library.usi.edu/record/1432895},
      doi = {https://doi.org/10.1007/978-981-15-8546-3},
}