Premium
Decision support system in the design of steel moment‐resisting frames using a realistic cost model
Author(s) -
Choi Byoung Han,
Kim Young Moon
Publication year - 2009
Publication title -
the structural design of tall and special buildings
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.895
H-Index - 43
eISSN - 1541-7808
pISSN - 1541-7794
DOI - 10.1002/tal.467
Subject(s) - frame (networking) , computer science , optimal design , moment (physics) , function (biology) , genetic algorithm , decision support system , joint (building) , industrial engineering , mathematical optimization , engineering , artificial intelligence , structural engineering , machine learning , mathematics , telecommunications , physics , classical mechanics , evolutionary biology , biology
Structural design and performance evaluation involve complex decision‐making tasks that are both time and cost intensive. Decision support systems that combine engineer interaction with computer‐based tools to provide a joint cognitive decision‐making environment can significantly help engineers. In this study, computational approaches that can become part of such a decision support system are proposed. These approaches use simulation‐based design to assist engineers with the design of steel moment‐resisting frames (SMRFs). A genetic algorithm (GA)‐based optimization approach is presented for the design of SMRFs with rigid connections that enables designers to identify the best locations for rigid connections in a frame. The optimization approach uses a unique cost function to carry out a trade‐off study between overall cost and rigid connections. Unlike some studies that express the connection cost as a factor of the entire frame weight, in this study, the connections and their associated cost factors are explicitly represented at the member level in order to evaluate the cost of the connections associated with each beam. The optimization formulation is then modified in order to generate alternatives that will have a cost comparable to that of the optimal solution, and that also might be more suitable for design than the optimal solution. The proposed approach enables engineers to compare different solutions on the basis of a number of practical criteria for the decision of the final design. Copyright © 2008 John Wiley & Sons, Ltd.