BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Helsinki BEGIN:DAYLIGHT DTSTART:20260329T040000 TZOFFSETFROM:+0200 TZOFFSETTO:+0300 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20261025T030000 TZOFFSETFROM:+0300 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260609T051055Z UID:87C9F596-064A-4FE3-847C-15389874C64F DTSTART;TZID=Europe/Helsinki:20260602T100000 DTEND;TZID=Europe/Helsinki:20260602T110000 DESCRIPTION:This event is jointly sponsored by Finland Section Chapter CAS0 4\, Nanjing Section Chapter CH11261\, University of Oulu\, and Hong Kong P olytechnic University.\n\nDue to increased complexity of the systems\, cos t reduction and detail modeling of the systems\, the requirements of optim ization have been increased. The conventional methods\, which guarantee to provide the optimal solution\, fail to solve many practical problems due to several requirements of these methods. The most familiar conventional o ptimization techniques fall in two categories viz. calculus based method a nd enumerative schemes. Though well developed\, these techniques possess s ignificant drawbacks. Calculus based optimization generally relies on cont inuity assumptions and existence of derivatives. Enumerative techniques re ly on special convergence properties and auxiliary function evaluation. Mo reover\, these optimizations are generally single path search and stuck wi th the local optima.\n\nIntelligent based optimization methods such as gen etic algorithm (GA)\, particle warm optimization (PSO)\, bacteria foraging \, ant colony\, neural networks\, etc. are multi-path search and provide s olution near to the global optima. They do not require derivatives of obje ctive function and constraints. This presentation briefly covers some of t he important techniques of optimization along with scope and future challe nges.\n\nSpeaker(s): Singh\, \n\nVirtual: https://events.vtools.ieee.org/m /561926 LOCATION:Virtual: https://events.vtools.ieee.org/m/561926 ORGANIZER:shuai.li@oulu.fi SEQUENCE:7 SUMMARY:Intelligent System Applications in Solving Engineering Problems URL;VALUE=URI:https://events.vtools.ieee.org/m/561926 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-bottom: 0c m\; text-align: justify\; text-justify: inter-ideograph\; line-height: nor mal\;"><strong><span lang="EN-US" style="font-size: 12.0pt\; mso-bidi-font -size: 11.0pt\; font-family: 'Times New Roman'\,serif\;">This event is joi ntly sponsored by Finland Section Chapter CAS04\, Nanjing Section Chapter CH11261\, University of Oulu\, and Hong Kong Polytechnic University.</span ></strong></p>\n<p class="MsoNormal" style="margin-bottom: 0cm\; text-alig n: justify\; text-justify: inter-ideograph\; line-height: normal\;">&nbsp\ ;</p>\n<p class="MsoNormal" style="margin-bottom: 0cm\; text-align: justif y\; text-justify: inter-ideograph\; line-height: normal\;"><span lang="EN- US" style="font-size: 12.0pt\; mso-bidi-font-size: 11.0pt\; font-family: ' Times New Roman'\,serif\;">Due to increased complexity of the systems\, co st reduction and detail modeling of the systems\, the requirements of opti mization have been increased. The conventional methods\, which guarantee t o provide the optimal solution\, fail to solve many practical problems due to several requirements of these methods.&nbsp\;</span><span lang="EN-US" style="font-size: 12.0pt\; font-family: 'Times New Roman'\,serif\;">The m ost familiar conventional optimization techniques fall in two categories v iz. calculus based method and enumerative schemes. Though well developed\, these techniques possess significant drawbacks. Calculus based optimizati on generally relies on continuity assumptions and existence of derivatives . Enumerative techniques rely on special convergence properties and auxili ary function evaluation. Moreover\, these optimizations are generally sing le path search and stuck with the local optima.&nbsp\;</span></p>\n<p clas s="MsoNormal" style="margin-bottom: 0cm\; text-align: justify\; text-justi fy: inter-ideograph\; line-height: normal\;"><span lang="EN-US" style="fon t-size: 12.0pt\; font-family: 'Times New Roman'\,serif\;">Intelligent base d optimization methods such as genetic algorithm (GA)\, particle warm opti mization (PSO)\, bacteria foraging\, ant colony\, neural networks\, etc. a re multi-path search and provide solution near to the global optima. They do not require derivatives of objective function and constraints. This pre sentation briefly covers some of the important techniques of optimization along with scope and future challenges.</span></p> END:VEVENT END:VCALENDAR