02008nam0 22004453i 450 VAN018337920230612024305.61N978331954241620210715d2017 |0itac50 baengCH|||| |||||Complex Networks VIIIProceedings of the 8th Conference on Complex Networks CompleNet 2017edited by Bruno Gonçalves ... [et al.]ChamSpringer2017xiv, 262 p.ill.24 cm001VAN01332982001 Springer Proceedings in Complexity210 Berlin [etc.]SpringerVAN0183390Complex Networks VIII182549968-XXComputer science [MSC 2020]VANC019670MF68TxxArtificial intelligence [MSC 2020]VANC021266MF00BxxConference proceedings and collections of articles [MSC 2020]VANC021742MFCOMPLENETKW:KComplex NetworksKW:KComplexity proceedingsKW:KComputational IntelligenceKW:KConference on Complex NetworksKW:KNetwork ScienceKW:KNetwork controllabilityKW:KRecommendation systemsKW:KCHChamVANL001889GonçalvesBrunoVANV107574International Workshop on Complex Networks8.2017Dubrovnik, CroatiaVANV164298Springer <editore>VANV108073650ITSOL20240614RICAhttp://doi.org/10.1007/978-3-319-54241-6E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICAIT-CE0120VAN08NVAN0183379BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08CONS e-book 3070 08eMF3070 20210715 Complex Networks VIII1825499UNICAMPANIA03694nam 22006615 450 991048411650332120200703072816.03-030-15050-X10.1007/978-3-030-15050-1(CKB)4100000008618154(MiAaPQ)EBC5811730(DE-He213)978-3-030-15050-1(PPN)243770243(EXLCZ)99410000000861815420190706d2019 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierActive Robust Optimization: Optimizing for Robustness of Changeable Products /by Shaul Salomon1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (175 pages)Springer Theses, Recognizing Outstanding Ph.D. Research,2190-50533-030-15049-6 Introduction -- Background -- Active Robust Optimization -- Active Robust Multi-Objective Optimization -- Case Studies -- Conclusions -- Appendix: Calculation of the qϵ+ Indicator.This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a “changeable product,” the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these ‎with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.Springer Theses, Recognizing Outstanding Ph.D. Research,2190-5053Automatic controlMathematical optimizationArtificial intelligenceManufacturesRoboticsAutomationControl and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Optimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26008Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Manufacturing, Machines, Tools, Processeshttps://scigraph.springernature.com/ontologies/product-market-codes/T22050Robotics and Automationhttps://scigraph.springernature.com/ontologies/product-market-codes/T19020Automatic control.Mathematical optimization.Artificial intelligence.Manufactures.Robotics.Automation.Control and Systems Theory.Optimization.Artificial Intelligence.Manufacturing, Machines, Tools, Processes.Robotics and Automation.519.6519.3Salomon Shaulauthttp://id.loc.gov/vocabulary/relators/aut1225589BOOK9910484116503321Active Robust Optimization: Optimizing for Robustness of Changeable Products2845518UNINA