A near-optimum multi-objective optimization approach for structural design
| dc.contributor.author | Okasha ,Nader M. | |
| dc.contributor.author | Alzo’ubi ,Abdel Kareem | |
| dc.contributor.author | Mughieda,Omer | |
| dc.contributor.author | Kewalramani ,Manish | |
| dc.contributor.author | Almasri ,Amin H. | |
| dc.date.accessioned | 2024-02-02T06:42:13Z | |
| dc.date.available | 2024-02-02T06:42:13Z | |
| dc.date.issued | 2024 | |
| dc.description | In the process of structural design, the designed system and its elements are configured to provide adequate levels of strength while minimizing cost. The strength provided by the configured system, and its elements must ensure acceptable levels of safety, serviceability, and stability. Meanwhile, any additional increase in strength and safety that can be achieved is encouraged. Hence, maximizing strength and minimizing cost are two desired criteria in structural design optimization. However, even though these two criteria may intuitively seem to be generally conflicting, the relationship between them is not straightforward. For instance, while the American Institute of Steel Construction (AISC) [1] standard wide flange section W24 × 62 has nearly half the weight of section W10 × 112, it has a larger plastic section modulus. Accordingly, considering safety against plastic bending failure, the former section is superior to the latter in both cost and strength. On the other hand, section W24 × 62 has both lower weight and lower plastic section modulus than W24 × 68. Thus, one section is superior in cost, while the other is superior in strength (again, considering plastic bending failure). These two examples highlight the complexity of the relationship between these two design criteria. | |
| dc.description.abstract | Multi-objective design optimization problems offer a set of solution alternatives within a Pareto-front. In structural design, the design variables are typically the section properties. The outcomes of these design variables are usually used in selecting standard sections. However, the properties of the selected standard sections normally have different values from the determined design variables. Accordingly, the values of the objective functions for these solutions will change after selecting standard sections. This change may be different among these solutions. Thus far, only Pareto-optimal solutions have been standardized in the literature. The effects of the inclusion of non-Pareto solutions in the standardization process have never been examined. In this paper, the differences between including the near-optimal solutions and not including them in the final structural design optimization set are explored. The paper investigates the impact of selecting standard sections on both Paretofront solutions and near-optimal solutions, and it studies the importance of keeping track of the near-optimal solutions. A modified version of a multiple-objective particle swarm optimization method, enhanced with a proposed computationally efficient section standardization algorithm, is used to solve multi-objective systemreliability design optimization problems. The concepts of the paper are applied to examples of bridge structures. The results demonstrate the efficiency of the proposed technique in capturing final design solutions that would have been otherwise missed due to standardization. Keywords: Multiple Design Options (MDO), Multi-Objective Particle Swarm Optimization (MDO-MOPSO) , System reliability, Structural design, Bridges | |
| dc.identifier.citation | Okasha, N. M., Alzo'ubi, A. K., Mughieda, O., Kewalramani, M., & Almasri, A. H. (2024). A near-optimum multi-objective optimization approach for structural design. Ain Shams Engineering Journal, 15(2), 102388. | |
| dc.identifier.doi | https://doi.org/10.1016/j.asej.2023.102388 | |
| dc.identifier.uri | https://dspace.adu.ac.ae/handle/1/770 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.title | A near-optimum multi-objective optimization approach for structural design | |
| dc.type | Article |