2 results listed
In this study, a nonparametric new test is proposed to test the hypothesis of equality of
locations against umbrella alternatives. The Shan test for ordered alternatives is adapted to the
umbrella alternatives. This test can be considered as an extension of the sign test and the Wilcoxon
signed rank test. By a comprehensive simulation study, the proposed test is compared with the
Mack-Wolfe and Hettmansperger and Norton tests in terms of type I error rate and power. The
simulation results showed that all tests ensured the Bradley's robustness criteria for type I error
rate. The power comparison results indicated that the proposed test gives better results than the
other tests.
International Data Science & Engineering Symposium
IDSES
Bülent ALTUNKAYNAK
Hamza GAMGAM
Merve BAĞÇACI
Multi-objective optimization problems allow multiple purpose to be simultaneously
optimized. The nondominated sorting genetic algorithm II (NSGA-II), which is one of the most
effective multi-objective heuristic methods in the solution of multi-objective optimization
problems, is widely used in the literature. NSGA-II obtains a Pareto optimal solutions, known as
a set of dominant solutions without requiring any prior knowledge in one run. The NSGA-II is
more useful than the classical genetic algorithm, minimizing the computational complexity by
calculating the fast dominated sorting approach and the crowded distance without having to repeat
for each solution. In this study, NSGA-II method was used to optimize the cutting parameters of
hard materials turning. In the experimental studies, the regression models based on the cutting
velocity, feed rate and depth of cut parameters represent three different objective functions. This
optimization problem, which has five objective functions with three variables, has been discussed
by NSGA-II method. The optimal solution of these functions is to use the NSGA-II method to find
the most suitable set of Pareto solutions. The solutions obtained by using NSGAII method have
been found to be successful in multi-objective optimization problems. In addition, decision makers
from the optimal solutions can choose the most suitable solution according to their importance in
the objective functions.
International Data Science & Engineering Symposium
IDSES
Ahmet KOCATÜRK
Bülent ALTUNKAYNAK