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Wasuwat Petprakob. Beam-slab floor optimization using genetic and particle swarm optimization algorithms. Master's Degree(Engineering and Technology). Thammasat University. Thammasat University Library. : Thammasat University, 2014.
Beam-slab floor optimization using genetic and particle swarm optimization algorithms
Name: Wasuwat Petprakob
keyword:
Beam-slab floor optimization
LCSH:
Floors
-- Design and construction
LCSH:
Building layout
LCSH:
Genetic algorithms
Abstract:
In this study, genetic and particle swarm optimization algorithms for beam-slab floor optimization are proposed. In order to construct the algorithms, the heuristic beam and beam-column layout design tasks are converted into algorithmic design tasks in two different ways. In the first way, heuristic rules are created for the beam-column layout design task. In the second way, the beam layout design task is merged with detailed designs of slabs and beams in order to obtain one algorithmic beam-slab design task. In the first alternative, two genetic algorithms are created. The first one is used to perform beam layout design by using heuristic rules. The second one is used to perform column layout design by using the result obtained from the first algorithm and also another set of heuristic rules. From the example problems, the results obtained from the two genetic algorithms are found to be satisfactory. The obtained layouts are found to be practical layouts that can be used in real practice. In the second alternative where the beam layout design task is merged with detailed designs of slabs and beams, the scope of this study is limited to those cases where the positions of columns are prescribed. The main objective of the whole beam-slab design task obtained from merging is simply the cost of steel beams. The employed design constraints are taken from the design specifications for flexure and shear in the ANSI/AISC 360-10 specification. Beam sections are selected from TIS 1227-1996. In the cost-based floor optimization, two phases of optimization are used. The first phase is for beam layout design, and the second phase is for beam sizing design. The best beam layout obtained from the first phase is used as an input layout for the second phase. A multi-population genetic algorithm is developed for beam layout design. A multi-population genetic algorithm and a multi-population binary particle swarm optimization algorithm are developed for beam sizing design. From the example problems, the results obtained from the proposed algorithms are found to be satisfactory
Thammasat University. Thammasat University Library
Address:
BANGKOK
Email:
preserv@tu.ac.th
Name: Pruettha Nanakorn
Role:
advisor
Created:
2014
Modified:
2021-12-29
Issued:
2021-12-29
วิทยานิพนธ์/Thesis
application/pdf
eng
DegreeName: Master of Science
Level: Master's Degree
Descipline: Engineering and Technology
Grantor: Thammasat University
©copyrights Thammasat University
RightsAccess:
ใช้เวลา
0.016273 วินาที
Wasuwat Petprakob
| Title | Contributor | Type |
|---|---|---|
| Beam-slab floor optimization using genetic and particle swarm optimization algorithms
มหาวิทยาลัยธรรมศาสตร์ Wasuwat Petprakob | Pruettha Nanakorn | วิทยานิพนธ์/Thesis |
Pruettha Nanakorn