دانلود رایگان مقاله بهینه سازی خرپا-Z چند شاخه بر اساس استراتژی تکامل

Abstract

This paper concerns multi-branch Truss-Z networks (MTZ). A possible scenario for creating a “multibranch bridge” linking 6 terminals of pedestrian and cycling communication is presented. This process is formulated as a constrained minimization problem. New, biology-inspired nomenclature for MTZ and encoding for MTZ are introduced. Several operations for MTZs are introduced and illustrated. The functionality of these operations is illustrated with transformation from a random MTZ to a “proper” 6-branch MTZ network. A population-based heuristic experiment is presented to demonstrate that the introduced operators allow us to create any desirable MTZ. A cost function for the considered scenario is introduced. The genetic operations are interpreted and visualized. A number of feasible MTZ layouts produced by an evolution strategy-based algorithm are presented. One of these layouts is used for creation of the spatial 6-terminal MTZ, which is also visualized.

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.