## 4 Case Illustration
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & & **S6** & & **S8** & & **S9** \\ \cline{3-8}
**SBU** & \(\mathbf{D_{i}}\) & \(\mathbf{x_{i}}\) & **Busy** & **Idle** & **Busy** & **Idle** & **Busy** & **Idle** \\ \hline A & 81 & 81 & 2997 & 38,763 & 3564 & 38,196 & 2916 & 38,844 \\ B & 52 & 52 & 2236 & 36,527 & 2652 & 35,544 & 2184 & 36,660 \\ C & 57 & 57 & 2850 & 33,677 & 3477 & 32,067 & 2793 & 33,867 \\ E & 69 & 69 & 4761 & 28,916 & 5727 & 26,340 & 4623 & 29,244 \\ D & 290 & 290 & 15,950 & 12,966 & 19,430 & 6910 & 15,660 & 13,584 \\ G & 63 & 51 & 5661 & 7305 & 6783 & 127 & 5508 & 8076
Step B12: Under the given conditions, the \(P\) and \(Q\) candidates are set as introduced in Table 6.  
Step B13: Considering the product mix from the MPS obtained in Step B10, the loops of neighbouring moves commence. Finally, the profits achieved in the iterations are compared, and the product mix that provides the highest profit is identified as the optimal product mix. After this point, the AHP-TOC heuristic terminates. Step B13 yielded an optimal product mix at the 7 th and 11 th iteration of the total 31 neighborhood space, where \(\varphi\) = 1, n = 5, \(\alpha\) = 0, \(\delta\) = 0, and \(\tau\) = 31, as in Table 7.  
From this point on, the solution procedure moves on to the GE/McKinsey product portfolio analysis procedure, in order to formulate the product portfolio strategies. By including the scores from the collected questionnaires, the pairs of market attractiveness and competitive strength for each SBU are calculated. The resulting scores are given in Table 8.  
From the company where the case study was conducted, three product portfolio questionnaires were collected for each SBU. After the required manipulations of the resulting survey data, the GE/McKinsey matrix took shape, as pictorially illustrated in Figure 4. \begin{table}
\begin{tabular}{l l l l l l l l l l l l l} \hline \hline
**Sequence** & **Step** & & & & & & & & & & & \\ \hline seq1 & A03 & A & \(>\) & B & \(>\) & C & \(>\) & E & \(>\) & D & \(>\) & G & \(>\) & F \\ seq2 & B09 & G & \(>\) & A & \(>\) & B & \(>\) & F & \(>\) & E & \(>\) & C & \(>\) & D \\ \hline Q Candidates \(\rightarrow\) & Q1 & & & & & & Q2 & & & & & & \\ P Candidates & & & & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Identification of the \(Q\) candidates. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & & **P Candidates** & & & & **Q Candidates** & & & & \\ \hline
**Iteration** & **D** & **C** & **E** & **B** & **A** & **G** & **F** & **S8** & **Profit** & **Tabu** \\ \hline
0 & 290 & 57 & 69 & 52 & 81 & 51 & 0 & 127 & 1,917,100 & \\
1 & 289 & 57 & 69 & 52 & 81 & 52 & 0 & 61 & 1,919,700 & \\
2 & 290 & 56 & 69 & 52 & 81 & 52 & 0 & 55 & 1,919,700 & \\
3 & 290 & 57 & 68 & 52 & 81 & 52 & 0 & 77 & 1,918,900 & X \\
4 & 290 & 57 & 69 & 51 & 81 & 52 & 0 & 45 & 1,919,750 & \\
5 & 290 & 57 & 69 & 52 & 80 & 52 & 0 & 38 & 1,919,800 & \\
6 & 289 & 56 & 69 & 52 & 81 & 52 & 1 & 19 & 1,920,800 & \\
7 & 290 & 56 & 68 & 52 & 81 & 53 & 0 & 5 & 1,921,500 & \\
8 & 290 & 57 & 68 & 51 & 81 & 52 & 1 & 25 & 1,920,050 & X \\
9 & 290 & 57 & 69 & 51 & 80 & 52 & 0 & 89 & 1,916,950 & X \\
10 & 289 & 57 & 69 & 52 & 80 & 52 & 1 & 2 & 1,920,900 & X \\
11 & 289 & 57 & 68 & 52 & 81 & 53 & 0 & 11 & 1,921,500 & \\
12 & 290 & 56 & 69 & 51 & 81 & 52 & 1 & 3 & 1,920,850 & X \\
31 & 289 & 56 & 68 & 51 & 80 & 54 & 0 & 34 & 1,918,450 & X \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Neighboring moves of one-way TS and change in profit. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & **Market** & **Competitive** & & **D1** & **Importance** & **Importance Order** \\  & **Attractiveness** & **Strength** & & & **Value** & & & \\ \hline A & 4.5 & 3 & 81 & 3.75 & 5 \\ B & 4.4 & 3.5 & 52 & 3.95 & 4 \\ C & 5.9 & 5 & 57 & 5.45 & 2 \\ D & 6.2 & 6 & 290 & 6.10 & 1 \\ E & 5.3 & 4.6 & 69 & 4.95 & 3 \\ F & 4.55 & 2.2 & 84 & 3.37 & 7 \\ G & 5.5 & 1.5 & 63 & 3.50 & 6 \\ \hline \hline \end{tabular}
\end{table}