Simulated Annealing (SA) algorithm is used to search the best solution for aircraft to execute.
A comprehensive optimization method based on GTHA is also developed to search the best solution efficiently.
Note that the proposed method needs to search the best solution among k·q possible candidates for each block (see steps c and d).
For dodging the difficulty of the FLP-based model to treat large-sized instances of NP-hard RCPSP, the permutation representation scheme of the PABC algorithm is in turn introduced utilizing the artificial bee colony (ABC) process to search the best solution for RCPSP.
A multi-objective genetic algorithm (MOGA), combined with improving heuristics, was developed to search the best solutions (Pareto optimums).
Considering this, the genetic algorithm is used to solve this problem by searching for the best solution from many initial points and obtaining the optimum solution by means of crossover and mutation operators [36, 37].
The solution of the problem results from an iterative process of searching for the best solution, that is, the one that, with the least amount of steel used, fulfills all the requirements: resistance, stability and displacement limits established by the current regulation.
This situation is beneficial in complex problems, because along the iterative process, the proposed algorithm improves their capabilities to search for the best solution.
