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SUMMARY:Producing Smart Pareto Sets for Multi-Objective Topology Optimisat
 ion Problems - David Munk\, The University of Sydney\, Australia
DTSTART:20170601T100000Z
DTEND:20170601T110000Z
UID:TALK72288@talks.cam.ac.uk
CONTACT:Mari Huhtala
DESCRIPTION:To date the design of structures via topology optimisation met
 hods has mainly focused on single-objective problems. However\, real-world
  design problems usually involve several different objectives\, most of wh
 ich counteract each other. This work presents an updated smart normal cons
 traint method\, which is combined with a bi-directional evolutionary struc
 tural optimisation algorithm for multi-objective topology optimisation. Th
 e smart normal constraints method has been modified by further restricting
  the feasible design space for each optimisation run such that dominant an
 d redundant points are not found. The algorithm is tested on several diffe
 rent structural optimisation problems. A number of different structural ob
 jectives are analysed\, namely compliance\, dynamic and buckling objective
 s. Therefore\, the method is shown to be capable of solving various types 
 of multi-objective structural optimisation problems. The goal of this work
  is to show that smart Pareto sets can be produced for complex topology op
 timisation problems. Furthermore\, this research hopes to highlight the ga
 p in the literature of topology optimisation for multi-objective problems.
LOCATION:Oatley 1 Meeting Room\, Floor 2\, Baker Building\, Cambridge Univ
 ersity Engineering Department
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