Aminbakhsh, Saman

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/6691
Name Variants
Saman, Aminbakhsh
S., Aminbakhsh
A., Saman
Saman Aminbakhsh
S.,Aminbakhsh
Aminbakhsh,Saman
A.,Saman
Aminbakhsh, Saman
Aminbakhsh,S.
Job Title
Doktor Öğretim Üyesi
Email Address
saman.aminbakhsh@atilim.edu.tr
Main Affiliation
Civil Engineering
Status
Website
ORCID ID
0000-0002-4389-1910
Scopus Author ID
55768552300
Turkish CoHE Profile ID
8D50169F8600DF9B
Google Scholar ID
JRu69LMAAAAJ
WoS Researcher ID
LIF-9792-2024

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
1
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
1
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents

15

Citations

632

h-index

8

Go to Scopus profile
Documents

16

Citations

532

Go to WoS profile
Scholarly Output

16

Articles

12

Views / Downloads

130/1606

Supervised MSc Theses

2

Supervised PhD Theses

0

WoS Citation Count

118

Scopus Citation Count

109

Patents

0

Projects

0

WoS Citations per Publication

7.38

Scopus Citations per Publication

6.81

Open Access Source

5

Supervised Theses

2

JournalCount
Journal of Construction Engineering, Management & Innovation2
Structures2
European Journal of Operational Research1
Journal of Building Engineering1
Journal of Construction Engineering and Management1
Current Page: 1 / 3

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

2021 - 20222
Reset filters

Settings

Has files: falseSubject: High-dimensional optimization

Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Article
    Citation - WoS: 12
    Citation - Scopus: 13
    E-Constraint Guided Stochastic Search With Successive Seeding for Multi-Objective Optimization of Large-Scale Steel Double-Layer Grids
    (Elsevier, 2022) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Kazemzadeh Azad, Saeid
    This paper proposes a design-driven structural optimization algorithm named e-constraint guided stochastic search (e-GSS) for multi-objective design optimization of large-scale steel double-layer grids having numerous discrete design variables. Based on the well-known e-constraint method, first, the multi-objective optimization problem is transformed into a set of single-objective optimization problems. Next, each single-objective optimization problem is tackled using an enhanced reformulation of the standard guided stochastic search algorithm proposed based on a stochastic maximum incremental/decremental step size approach. Moreover, a successive seeding strategy is employed in conjunction with the proposed e-GSS algorithm to improve its performance in multi-objective optimization of large-scale steel double-layer grids. The numerical results obtained through multi-objective optimization of three challenging test examples, namely a 1728-member double-layer compound barrel vault, a 2304-member double-layer scallop dome, and a 2400-member double-layer multi-radial dome, demonstrate the usefulness of the proposed e-GSS algorithm in generating Pareto fronts of the foregoing multi-objective structural optimization problems with up to 2400 distinct sizing variables.
  • Thumbnail Image
    Article
    Citation - WoS: 25
    Citation - Scopus: 32
    High-Dimensional Optimization of Large-Scale Steel Truss Structures Using Guided Stochastic Search
    (Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Kazemzadeh Azad, Saeid
    Despite a plethora of truss optimization algorithms devised in the recent literature of structural optimization, still high-dimensional large-scale truss optimization problems have not been properly tackled basically due to the excessive computational effort required to handle the foregoing instances. In this study, application of a recently developed design-driven heuristic, namely guided stochastic search (GSS), is extended to a more challenging class of truss optimization problems having thousands of design variables. Two variants of the algorithm, namely GSSA and GSSB, have been employed for sizing optimization of four high-dimensional examples of steel trusses, i.e., a 2075-member single-layer onion dome, a 2688-member double-layer open dome, a 6000-member doublelayer scallop dome, and a 15048-member double-layer grid as per AISC-LRFD specification. The numerical results obtained indicate the efficiency of GSSA and GSSB in handling high-dimensional instances of large-scale steel trusses with up to 15048 discrete design variables.