LEADER 05198nam 22006255 450 001 9910299896903321 005 20200704080731.0 010 $a3-319-64063-1 024 7 $a10.1007/978-3-319-64063-1 035 $a(CKB)4100000000586796 035 $a(DE-He213)978-3-319-64063-1 035 $a(MiAaPQ)EBC5592300 035 $a(PPN)204534097 035 $a(EXLCZ)994100000000586796 100 $a20170913d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNEO 2016 $eResults of the Numerical and Evolutionary Optimization Workshop NEO 2016 and the NEO Cities 2016 Workshop held on September 20-24, 2016 in Tlalnepantla, Mexico /$fedited by Yazmin Maldonado, Leonardo Trujillo, Oliver Schütze, Annalisa Riccardi, Massimiliano Vasile 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XIII, 282 p. 146 illus., 124 illus. in color.) 225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v731 311 $a3-319-64062-3 320 $aIncludes bibliographical references and index. 327 $aPart I: Smart Cities -- Defensive Driving Strategy and Control for Autonomous Ground Vehicle in Mixed Traf?c -- Augmenting the LSA Technique to Evaluate Ubicomp Environments -- Mixed Integer Programming Formulation for the Energy-Ef?cient Train Timetables Problem -- Distributing Computing in the Internet of Things: Cloud, Fog and Edge Computing Overview -- Part II: Search, Optimization and Hybrid Algorithms -- Integer Programming Models and Heuristics for Non-Crossing Euclidean 3-Matchings -- A Multi-Objective Robust Ellipse Fitting Algorithm -- Gradient-Based Multiobjective Optimization with Uncertainties -- A New Local Search Heuristic for the Multidimensional Assignment Problem -- Part III: Electronics and Embedded Systems --  A Multi-Objective and Multidisciplinary Optimisation Algorithm for Microelectromechanical Systems -- Coef?cients Estimation of MPM through LSE, ORLS and SLS for RF-PA Modeling and DPD -- Optimal Sizing of Ampli?ers by Evolutionary Algorithms with Integer Encoding and gm/ID Design Method -- Index.  . 330 $aThis volume comprises a selection of works presented at the Numerical and Evolutionary Optimization (NEO 2016) workshop held in September 2016 in Tlalnepantla, Mexico. The development of powerful search and optimization techniques is of great importance in today?s world and requires researchers and practitioners to tackle a growing number of challenging real-world problems. In particular, there are two well-established and widely known ?elds that are commonly applied in this area: (i) traditional numerical optimization techniques and (ii) comparatively recent bio-inspired heuristics. Both paradigms have their unique strengths and weaknesses, allowing them to solve some challenging problems while still failing in others. The goal of the NEO workshop series is to bring together experts from these and related ?elds to discuss, compare and merge their complementary perspectives in order to develop fast and reliable hybrid methods that maximize the strengths and minimize the weaknesses of the underlying paradigms. In doing so, NEO promotes the development of new techniques that are applicable to a broader class of problems. Moreover, NEO fosters the understanding and adequate treatment of real-world problems particularly in emerging ?elds that affect all of us, such as healthcare, smart cities, big data, among many others. The extended papers presented in the book contribute to achieving this goal.   . 410 0$aStudies in Computational Intelligence,$x1860-949X ;$v731 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aOptical data processing 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aOptical data processing. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 676 $a519.3 702 $aMaldonado$b Yazmin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTrujillo$b Leonardo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSchütze$b Oliver$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRiccardi$b Annalisa$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVasile$b Massimiliano$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299896903321 996 $aNEO 2016$92501311 997 $aUNINA