## A presentation of several simplex optimization techniques |

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### Contents

THE SIMPLEX METHOD OF NELDER AND MEAD | 5 |

REFLECTION IN A DIRECTION AS DETERMINED | 13 |

REFLECTION CLOSER TO THE VERTICES HAVING | 16 |

7 other sections not shown

### Common terms and phrases

330 OOOE+Ol OOOE+Ol 360 OOOE+Ol 810 CONTINUE ALGOL area of search Chebyquad CONTINUE DO 63 CONTINUE RETURN END current simplex elements Equation estimation EVAL evaluate f(x exponential weighting FUNC GO TO 21 GO TO 64 go to step GO TQ gradient Hessian matrix HIGHEST FUNCTION VALUE IF(MOncHK.EQ.l initial simplex iteration LEAST=1 linear search Mead's method method of Nelder method presented methods G MODBAD»l modification Nelder and Mead number of dimensions number of function Numerical results objective function OOOE+01 OOOE+01 OOOE+Ol 78 OOOE+Ol 81 OOOE+Ol OOOE+Ol 000E+C1 optimization techniques past samples performance indices performance measure PMIN presented in Chapter priori knowledge Proceed to step PSTORE quadratic approximations quadratic function rate of convergence Refer to Figure reflection step replace RETURN END FUNCTION return to step Rosenbrock search algorithm search method set MODBAD equal SIMPLEX METHOD SUBPROGRAM DETERMINES SUBPROGRAM PRODUCES Table test functions thesis tion tive value of f(x variables vertices