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Introduction to LS-OPT®


  • Im­ti­az Gandiko­ta


  • $650
  • $325 for students

What's Included

  • Two days of in­struc­tion
  • Class notes

Introduction to LS-OPT®


  • An in­tro­duc­to­ry class in LS-DY­NA® is rec­om­mend­ed but not nec­es­sary.


This course pro­vides an in­tro­duc­tion to the use of the op­ti­miza­tion code LS-OPT for de­sign. It cov­ers both the­o­ret­i­cal con­cepts and prac­ti­cal as­pects of de­sign op­ti­miza­tion. An em­pha­sis is placed on in­ter­fac­ing LS-OPT with LS-DY­NA. The course in­cludes work­shop ses­sions in which the cov­ered the­o­ret­i­cal top­ics are ap­plied. The LS-OPT graph­i­cal user in­ter­face is used to teach in­put prepa­ra­tion and post-pro­cess­ing.


  1. In­tro­duc­tion to de­sign op­ti­miza­tion us­ing in­dus­tri­al ex­am­ples
  2. LS-OPT fea­tures
  3. Op­ti­miza­tion the­o­ry
    1. Op­ti­miza­tion fun­da­men­tals
    2. Re­sponse sur­face method­ol­o­gy
    3. Ex­per­i­men­tal de­sign
    4. Meta­mod­el­ing
    5. De­sign mod­el ad­e­qua­cy check­ing
    6. Op­ti­miza­tion strate­gies
    7. Sen­si­tiv­i­ty analy­sis and vari­able screen­ing
  4. Set­ting up and run­ning a se­quen­tial op­ti­miza­tion
  5. Dis­crete op­ti­miza­tion
  6. Op­ti­miza­tion with user de­fined stage/­solver
  7. Im­port­ing analy­sis re­sults ta­ble
  8. Di­rect op­ti­miza­tion
  9. Pa­ra­me­ter iden­ti­fi­ca­tion us­ing curve match­ing
  10. Mul­ti­dis­ci­pli­nary Op­ti­miza­tion(MDO)
  11. Mode track­ing
  12. Vari­able screen­ing and MDO with re­duced vari­ables
  13. Mul­ti-Ob­jec­tive Op­ti­miza­tion (MOO) the­o­ry
  14. Set­ting up and run­ning MOO ex­am­ple - con­struct Pare­to Front
  15. Post-pro­cess­ing MOO prob­lems
    1. Trade-off plot
    2. Par­al­lel Co­or­di­nate Plot (PCP)
    3. Self-Or­ga­niz­ing Maps (SOM)
    4. Hy­per Ra­di­al Vi­su­al­iza­tion (HRV)