The generality of the genetic search in the light of proper coding schemes, together with its non‐gradient‐based search, has made it popular for many discrete problems including structural optimization. However, the required computational effort increases as the cardinality of the search space and the number of design variables increase. Memetic algorithms are formal attempts to reduce such a drawback for real‐world problems incorporating some kind of problem‐specific information. This paper aims to address this issue.
In this paper both Lamarckian and Baldwinian approaches for meme evolution are implemented using the power of graph theory in topology assessment. For this purpose, the concept of load path connectivity in frame bracing layouts is introduced and utilized by the proposed graph theoretical algorithms. As an additional search refinement tool, a dynamic mutation band control is recommended. In each case, the results are studied via a set of ultimate design family rather than one pseudo optimum. The method is further tested using a number of steel frame examples and its efficiency is compared with conventional genetic search.
Here, the problem of bracing layout optimization in steel frames is studied utilizing a number of topological guidelines.
The method of this paper attempts to reduce the computational effort for optimal design of real‐world problems incorporating some kind of problem‐specific information.
