# A Genetic Crow Search Algorithm for Optimization of Operation Sequencing in Process Planning
## 5 Case Studies
### Parameter Settings  
In order to achieve the best possible parameter settings for the GCSA approach, we applied the Taguchi design of experiments to optimize the input parameters. The Taguchi design of experiments uses orthogonal arrays to obtain a certain number of experiments that can provide information of all factors that affect the performance of some process as expressed by [PERSON] et al. [4]. Based on the input parameters of the GCSA and appropriate levels of variations, an experimental design matrix was formed using the standard L\({}_{32}\). Taguchi orthogonal array with 32 experimental trials. In the mentioned case studies at the input of the experimental design, the following GCSA parameters are varied: maximal number of iterations, flock size, awareness probability, flight length, tournament size and scale factors \(k_{c1}\), \(k_{c2}\), \(k_{m1}\) and \(k_{m2}\). Accuracy is increased by repeating every experiment 20 times. Therefore, the average result, the minimal result and the maximal result are used as the output parameters. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Feature Definition** & **Operations** & **Machines[]** & **Tools[]** & **TADs[]** & **Predecessors** \\ \hline F12—The top holes & Drilling (o21) & m9,m10 & t10 & -z,+z & o1,022,02,03,012, 09 \\ \hline F13—Top plane & Rough milling (o22) & m4,m5 & t7,48,t9 & -z & o1 \\ \hline F14—Counterbone & & & & & \\ hole & Spot facing (o23) & m9,m10 & t20 & -z & o1,022,02,03,027 \\ \hline F15—\(\diameter\)18H7 hole & Drilling (o24) & m9,m10 & t11 & +z & o1,022,02,03 \\  & Reaming (o25) & m9,m10 & t22 & +z & o1,022,02,03,034 \\ \hline F16—2-\(\diameter\)12.5 hole & Drilling (o26) & m9,m10 & t12 & +z & o1,022,02,03 \\ \hline F17—12-\(\diameter\)21 hole & Drilling (o27) & m9,m10 & t13 & +z & o1,022,02,03 \\ \hline F18—18-\(\diameter\)17 hole & Drilling (o28) & m9,m10 & t14 & +z & o1,022,02,03 \\ \hline F19—Side hole & Rough boring (o29) & m7,m8 & t6 & -y & o1,022,02,03 \\  & Finish boring (o30) & m6,m7,m8 & t6 & -y & o1,022,02,03 \\ \hline F20—5-\(\diameter\)20 hole & Drilling (o31) & m7,m8,m9,m10 & t15 & -a & o1,022,02,03,07,028 \\ \hline F21—24-\(\diameter\)8 hole & Drilling (o32) & m7,m8,m9,m10 & t16 & -a & o1,022,02,03,07,028 \\  & Tapping (o33) & m7,m8,m9,m10 & t23 & -a & o1,022,02,03,07,028,032 \\ \hline F22—Oil passage & Reaming (o34) & m6,m7,m8 & t28 & -c & o1,022 \\ hole 1 & Tapping (o35) & m6,m7,m8 & t24 & -c & o1,022,034 \\ \hline F23—Oil passage & Drilling (o36) & m6,m7,m8 & t17 & -c & o1,022 \\ hole 2 & Tapping (o37) & m6,m7,m8 & t25 & -c & o1,022,036 \\ \hline F24—\(\diameter\)23 & & & & & \\ Counterbore hole & Spot facing (o38) & m3,m4,m9,m10 & t21 & -z & o1,022,02,03,024,025 \\ \hline F25—Holes in & Drilling (o39) & m9,m10 & t18 & -b & o1,022,02,03,017, \\ inclined plane 1 & & & & & & o18,027,04 \\  & Tapping (o40) & m9,m10 & t26 & -b & o1,022,02,03,017, \\  & Tapping (o41) & m9,m10 & t26 & -b & o18,027,04,039 \\ \hline F26—Holes in & Drilling (o41) & m9,m10 & t18 & -b & o1,022,02,03,029, \\ inclined plane 2 & & & & & & o19,020 \\  & Tapping (o42) & m9,m10 & t26 & -b & o1,022,02,03,029, \\  & Tapping (o42) & m3,m4,m9,m10 & t18 & -z & o1,022,02,03,015,016 \\  & Tapping (o44) & m3,m4,m9,m10 & t26 & -z & o1,022,02,03,015,016,043 \\ \hline F28—Oil passage & Drilling (o45) & m6,m7,m8 & t19 & -x & o1,022,02,03,028 \\ hole 3 & Tapping (o46) & m6,m7,m8 & t27 & -x & o1,022,02,03,028, 045 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._Since the two cases significantly differ in dimensions, we formed two different experimental designs in terms of levels of variation to optimize the GCSA parameters for both. In that sense, the adopted levels of variation of Part 1 are: maximal number of iterations [400,1000], flock size [60,120], tournament size [2,5], \(k_{c1}\) [0.6, 0.9], \(k_{c2}\) [0.3, 0.6], \(k_{m1}\) [0.3, 0.6] and \(k_{m2}\) [0.1, 0.3]. In order to reduce the number of experiments, we applied \(L_{32}\) (\(2^{9}\)) orthogonal array, where 32 experiments are sufficient to make a conclusion.