


IOSO algorithms efficiency for stochastic optmization problemsComparison of several optimization methods’ efficiency
for solving stochastic problems

Testing conditions 
Comparative score 
The comparison was conducted using test functions collected by Dr. Eric Sandgren in his dissertation (Sandgren, Eric. “The Utility of Nonlinear Programming Algorithms”, a thesis submitted for the Degree of Doctor of Philosophy, Purdue Univercity, 1977). By superimposing the multiplicative numerical noise on the main function we simulated stochastic behavior. The numerical noise was distributed according to normal distribution: Y_{sto}=Y_{ini}*(1+N(0,s)).We compared four different optimization methods: IOSO (version IOSO NS 1.0); MFD  modified method of feasible directions; SQP  sequental quadratic programming; SLP  sequental linear programming. 

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