Lecture 35 - Simplex Search Algorithm | Minimum of a multivariable function numerically

[@vvr275]

Thank You It helps a lot

[@tasneemkazimahmuda7412]

Thanks! This is helpful.

[@avirupsinha]

Exam in 20 mins and I have started watching this 💀.. wish me luck! 💀💀💀

[@SukantaNayakedu]

Good luck!!

[@dharmiksaitallapalli5113]

Could u please post an example problem

[@samykhennache9510]

This is Nelder-Mead method, right? Not original simplex

[@devanshdewan2597]

yup

[@whitedevil8309]

Which book is this..? Can you suggest some good book related to this topic..

[@SukantaNayakedu]

From book 'Optimization for Engineering Design: Algorithms and Examples' You may also refer optimization by S. S. Rao and another is by Chong and Zak

[@harshalshrivasatava3584]

Thankyou so much sir

[@SukantaNayakedu]

Thank you for watching.

[@amritbirsingh8263]

what is gaama and beta

[@SukantaNayakedu]

gamma is expansion parameter and beta is contraction parameter. In minimization problem, when function value of reflected point is less than the function value of best point then gamma is used to find the new point. Other case negative and positive beta values are used. See the Lecture for details. Thank you.

[@JayantKumarZ]

first you say beta is between 0 to 1 then how can beta be negative? :(

[@SukantaNayakedu]

There are two conditions for contraction. Accordingly beta is negative and positive value. For example, if beta is 0.3 then if for one condition we take positive beta that is 0.3 and another condition negative beta that is -0.3 (if reflected point is worst than worst point).

[@JayantKumarZ]

@@SukantaNayakedu thanks :D

[@tasneemkazimahmuda7412]

@@SukantaNayakedu For two for the contraction conditions, if I use same beta value (one is positive and one is negative, for example: 0.3 and - 0.3), then Xnew in (ii) and (iii) become same! Am I missing something here?