8. Conclusions and future work
The new encoding for multi-branch Truss-Z (MTZ) introduced here is substantially more efficient than the previous encoding presented in [11]. It is not only more intuitive, but also more suitable for “genetic operations” and therefore – better suited for metaheuristic optimization methods. The genetic operators for MTZ introduced in this paper are efficient as demonstrated in numerous examples and the minimization experiments show good convergence. A 6-branch MTZ for linking 3 pedestrian/cycling paths has been presented. Although the structural considerations are not part of this paper, this modular 6-branch bridge can be considered relatively realistic. Primary experiments with crossover showed no benefit to the optimization algorithm, therefore have not been presented here. This was most likely due to the “harshness” of the procedure, which produces feasible individuals, but hardly resembling the parents. This phenomenon was also noticeable while calibrating the mutation intensity which also was relatively low (≤ 0.12). Nevertheless, elaboration of crossover is a natural direction for the future research. This paper presents a constrained optimization problem, however, the formal definition of the actual constraints was not necessary. Moreover, the problem of MTZ optimization has been simplified to the MTZ layout optimization. Therefore, a realistic three-dimensional case study where constraints are explicitly formulated is under consideration. Finally, the problem of intermediate supports has not been addressed sufficiently yet. However, this will be part of the design of the TZ prototype in the future.
