Table 2.

Pseudo-code of the eMOGOA model for TCCP.

Input: Number of solution (n) and maximum of iterations (L)

Begin Build project network; Generate randomized solution; while (stopping condition is not satisfied) do   Determine fitness score (Eq. (15), Eq. (16) and Eq. (17)); Phase 1: MOGOA process [     Update c value using Eq. (8) for (each solution i) do      Normalize the distances between solutions;      Update the position of current solution by Eq. (8) end ] Phase 2: TS-OBL process [    Determine the best solution through TS process for (each solution i) do     Update the position of current solution by Eq. (11)     Determine opposite solution of current solution by Eq. (14)     Determine superior solution between current solution and opposite solution end ]    Determine non-dominated solutions    Update new solution set Return: The best solution End

Output: The best solution and its score