LEADER 03384oam 2200517 450 001 9910483641203321 005 20210530212830.0 010 $a981-15-8546-6 024 7 $a10.1007/978-981-15-8546-3 035 $a(CKB)4100000011645266 035 $a(DE-He213)978-981-15-8546-3 035 $a(MiAaPQ)EBC6422733 035 $a(PPN)252512596 035 $a(EXLCZ)994100000011645266 100 $a20210530d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNonlinear interval optimization for uncertain problems /$fChao Jiang, Xu Han, Huichao Xie 205 $a1st ed. 2021. 210 1$aSingapore :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (XII, 284 p. 103 illus., 58 illus. in color.) 225 1 $aSpringer Tracts in Mechanical Engineering 311 $a981-15-8545-8 320 $aIncludes bibliographical references. 327 $aIntroduction -- Fundamentals of interval number theory -- Mathematical transformation models of nonlinear interval optimization -- Interval optimization based on hybrid optimization algorithms -- Interval optimization based on interval structural analysis -- Interval optimization based on sequential linear programming -- Interval optimization based on surrogate models -- Interval multidisciplinary optimization design -- Interval optimization based on a novel interval possibility degree model -- Interval optimization considering parameter dependences -- Interval multi-objective optimization design -- Interval optimization considering tolerance design -- Interval differential evolution algorithm. 330 $aThis book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods. 410 0$aSpringer tracts in mechanical engineering. 606 $aMathematical optimization 606 $aAerospace engineering 615 0$aMathematical optimization. 615 0$aAerospace engineering. 676 $a519.3 700 $aJiang$b Chao$01228285 702 $aHan$b Xu 702 $aXie$b Huichao 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a9910483641203321 996 $aNonlinear interval optimization for uncertain problems$92851535 997 $aUNINA