Aminbakhsh, Saman
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Saman, Aminbakhsh
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A., Saman
Saman Aminbakhsh
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Aminbakhsh,Saman
A.,Saman
Aminbakhsh, Saman
Aminbakhsh,S.
S., Aminbakhsh
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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
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Scopus Author ID
Turkish CoHE Profile ID
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WoS Researcher ID
Sustainable Development Goals
7
AFFORDABLE AND CLEAN ENERGY
1
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
14
LIFE BELOW WATER
1
Research Products
Documents
14
Citations
623
h-index
8
Documents
15
Citations
526
Scholarly Output
13
Articles
10
Views / Downloads
63/1110
Supervised MSc Theses
2
Supervised PhD Theses
0
WoS Citation Count
109
Scopus Citation Count
91
WoS h-index
5
Scopus h-index
4
Patents
0
Projects
0
WoS Citations per Publication
8.38
Scopus Citations per Publication
7.00
Open Access Source
3
Supervised Theses
2
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| Journal | Count |
|---|---|
| Journal of Construction Engineering, Management & Innovation | 2 |
| Structures | 2 |
| European Journal of Operational Research | 1 |
| Journal of Building Engineering | 1 |
| 20th International Conference on Computing in Civil and Building Engineering-ICCCBE -- AUG 25-28, 2024 -- Montreal, CANADA | 1 |
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13 results
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Master Thesis Türk İnşaat Sektöründe 3B Baski Teknolojisinin Benimsenmesini Etkileyen Ana Etkenler ve Engeller(2025) Latifiilkhechi, Leva; Aminbakhsh, Saman; Akçay, Emre CanerBu çalışmada, Türk inşaat sektöründe 3B baskı teknolojisinin benimsenmesini etkileyen temel faktörler incelenmiştir. Bu doğrultuda, kapsamlı bir literatür taraması sonucunda 27 teşvik edici ve 19 engelleyici faktör belirlenmiş olup, bu faktörlerin değerlendirmesi 106 uzmandan oluşan bir anket çalışması ile yapılmıştır. Bu faktörlerin önemi, Göreceli Önem İndeksi (GÖİ) kullanılarak değerlendirilmiş ve ardından Analitik Hiyerarşi Prosesi (AHP) ile faktörlerin önem düzeyleri belirlenmiştir. 3B baskı teknolojisinin daha hızlı inşaat, iş kazalarının azalması, enerji verimliliğinin artması ve karmaşık tasarımların daha kolay uygulanması gibi avantajlar sunduğu görülse de, bu teknolojinin benimsenmesini engelleyen başlıca zorluklar arasında 3B Beton Baskı için yeterli düzenlemelerin ve yapı kodlarının eksikliği, büyük ölçekli uygulamalar konusunda sınırlı bilgi ve yalıtım malzemelerinin yetersizliği yer almaktadır. Araştırma sonuçları, malzeme israfını azaltma ve daha fazla özelleştirme imkânı sağlama gibi faktörlerin 3B baskının inşaat sektöründe benimsenmesinde en önemli etmen olduğunu, gözetim maliyetlerinin azaltılmasının ise en az önemli teşvik edici faktör olduğunu ortaya koymuştur. Diğer yandan, siber güvenlik riskleri, potansiyel iş kayıpları ve basılı yapıların katmanlı ve pürüzlü yüzeyleri, en kritik engeller olarak belirlenmiştir. Bu araştırma, 3B baskı teknolojisinin inşaat sektörüne entegrasyonunun artırılması için bu etmenlerin ve engellerin hedefe yönelik stratejilerle ele alınması gerektiğini vurgulamaktadır.Article Effects of Topological Structure of Project Network on Computational Cost(Golden Light Publ, 2024) Aminbakhsh, SamanUnderstanding how network complexity affects optimization algorithms is crucial for improving computational efficiency. This study investigates how variations in network complexity impact the performance of optimization algorithms. By examining networks with different serial/parallel indicator (I2) values, the research uncovers several key insights into how topology influences computational requirements. The experiments show that higher I2 values, which are closer to serial configurations, heighten the problem's complexity. This study reveals that networks with lower I2 values, which exhibit steeper time-cost curves with fewer solutions over their efficient frontiers, require significantly more CPU time, indicating that project complexity does not necessarily scale with the extend of the Pareto fronts. This contradicts the expectation that more Pareto front solutions would inherently demand greater computational resources. Lastly, the study highlights that while the number of time-cost realizations is often used to gauge project complexity, it may not be conclusive on its own and that one complexity measure can outperform another. Although it can be an effective indicator, it does not fully capture the computational challenges posed by different network topologies. This study further acknowledges the difficulty in establishing a clear link between project performance and complexity due to the multifaceted nature of the problem. The findings suggest that exploring similar problems in other contexts could provide valuable insights into understanding and managing computational complexity.Article Citation - WoS: 25Citation - Scopus: 32High-Dimensional Optimization of Large-Scale Steel Truss Structures Using Guided Stochastic Search(Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, SamanDespite 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.Article Citation - Scopus: 1An Enhanced Guided Stochastic Search With Repair Deceleration Mechanism for Very High-Dimensional Optimization Problems of Steel Double-Layer Grids(Springer, 2024) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Gandomi, Amir H.Finding reasonably good solutions using a fewer number of objective function evaluations has long been recognized as a good attribute of an optimization algorithm. This becomes more important, especially when dealing with very high-dimensional optimization problems, since contemporary algorithms often need a high number of iterations to converge. Furthermore, the excessive computational effort required to handle the large number of design variables involved in the optimization of large-scale steel double-layer grids with complex configurations is perceived as the main challenge for contemporary structural optimization techniques. This paper aims to enhance the convergence properties of the standard guided stochastic search (GSS) algorithm to handle computationally expensive and very high-dimensional optimization problems of steel double-layer grids. To this end, a repair deceleration mechanism (RDM) is proposed, and its efficiency is evaluated through challenging test examples of steel double-layer grids. First, parameter tuning based on rigorous analyses of two preliminary test instances is performed. Next, the usefulness of the proposed RDM is further investigated through two very high-dimensional instances of steel double-layer grids, namely a 21,212-member free-form double-layer grid, and a 25,514-member double-layer multi-dome, with 21,212 and 25,514 design variables, respectively. The obtained numerical results indicate that the proposed RDM can significantly enhance the convergence rate of the GSS algorithm, rendering it an efficient tool to handle very high-dimensional sizing optimization problems.Article Citation - WoS: 5Resource Allocation Capabilities of Commercial Project Management Software Packages for Resource Leveling and Resource Constrained Project Scheduling Problems: a Comparative Study(Golden Light Publ, 2023) Albayati, Noor Hussein Farooq; Aminbakhsh, SamanIn construction project management the critical path method (CPM) is the most used technique for project scheduling. Although this technique provides many advantages for project managers, it cannot efficiently deal with the allocation of the resources. Therefore, alternative techniques have been introduced to address resource allocation requirements of the projects. Of these techniques, Resource Leveling (RLP) aims to minimize the fluctuation in resource usage histograms while maintaining the duration obtained by CPM. Resource Constrained Project Scheduling Problem (RCPSP), on the other hand, aims to secure the shortest CPM duration without violating the resource constraints. RLP and RCPSP are vital for effective utilization of project resources (e.g., manpower, machinery, and equipment) as they help precluding intermittent usage or over-allocation of the resources. Keeping the resource usage at a relatively constant level through RLP would result in a decrease in the overall project cost as the additional costs required to demobilize and remobilize the resources will be minimized. Shortening the makespan while meeting the resource constraints through RCPSP would lead to improved resource utilization and cost savings as well. The main objective of this study is, therefore, to analyze effectiveness and efficiency of the most widely used commercial project management software packages in solving resource allocation problems. To this end, the most recent versions - as per the date of this study - of three software packages, namely, Microsoft Project Professional 2019, Primavera P6 Professional 2019, and Asta Powerproject version 15.0.01.489 are examined. The performance of the practiced software is evaluated based on thirteen different priority rules over a set of problem instances available in the literature. The practiced problems include 640 instances providing a diverse combination of network complexity, activity number, and resource type number. Results obtained by the software for RCPSP are also compared with the solutions provided by the Serial Scheduling Scheme - a heuristic method. The findings of this study reveal that whilst all the three software packages manage to provide comparable results, Asta PowerProject transpire to be the all-round best performing method while Primavera sports the fastest leveling module. This study also sheds light on the challenges and practical hurdles to utilization of the aforementioned software for resource allocation purposes.Article Citation - WoS: 3Citation - Scopus: 2Ε-Constraint Procedures for Pareto Front Optimization of Large Size Discrete Time/Cost Trade-Off Problem(Elsevier, 2025) Aminbakhsh, Saman; Sonmez, Rifat; Atan, TankutThe discrete time/cost trade-off problem (DTCTP) optimizes the project duration and/or cost while considering the trade-off between activity durations and their direct costs. The complete and non-dominated time-cost profile over the set of feasible project durations is achieved within the framework of Pareto front problem. Despite the importance of Pareto front optimization in project and portfolio management, exact procedures have achieved very limited success in solving the problem for large size instances. This study develops exact procedures based on combinations of mixed-integer linear programming (MILP), epsilon-constraint method, network and problem reduction techniques, and present new bounding strategies to solve the Pareto problem for large size instances. This study also provides new large size benchmark problem instances aiming to represent the size of real-life projects for the DTCTP. The new instances, therefore, are generated to include up to 990 activities and nine execution modes. Computational experiments reveal that the procedures presented herein can remarkably outperform the state-of-the-art exact methods. The new exact procedures enabled obtaining the optimal Pareto front for instances with serial networks that include more than 200 activities for the first time.Conference Object Investigating the Barriers To the Adoption of 3d Printing Technology in the Turkish Construction Industry(Springer International Publishing Ag, 2025) Latifiilkhechi, Leva; Aminbakhsh, Saman; Akcay, Emre CanerIn recent years, 3D printing has emerged as a transformative force in construction technology. This innovative technology has found applications in many construction and bridge-building projects, starting a new era of automation and efficiency. Notably, the impact of 3D printing on the construction industry has been profound, yielding benefits such as reduced labor requirements, minimized material waste, accelerated project timelines, and a significant reduction in hazardous tasks for human workers. In contrast to conventional construction approaches, 3D printing stands out for its environmentally friendly characteristics, challenging traditional notions of geometric complexities and constraints in construction processes. While 3D printing technology undeniably offers a multitude of advantages over traditional methodologies, it is crucial to acknowledge that it also introduces its own set of unique challenges and risks. The main aim of this study is to investigate the barriers that hinder the adoption of 3D printing technology in the Turkish construction industry. Towards this, first, the list of potential barriers was extracted from multiple reputable sources, including Scopus, ScienceDirect and Web of Science databases. Based on this list, an online questionnaire was prepared to assess the impact of 19 potential barriers on the implementation of 3D printing technology in the Turkish construction industry. The findings and research directions articulated in this study create fresh pathways for further inquiry and substantial contributions to the evolving field of 3D printing in the construction industry.Article Citation - WoS: 11Citation - Scopus: 10Multi-Stage Guided Stochastic Search for Optimization and Standardization of Free-Form Steel Double-Layer Grids(Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Shaban, Samer S. S.There has been a growing interest in the use of free-form structures with irregularly curved yet aesthetically pleasing configurations in the recent decades. Although design optimization of regular steel grids has been well addressed in the literature of structural optimization, still limited work has been devoted to optimum design of real-size free-form grid structures. On the one hand, a main obstacle when dealing with real-size free-form steel grids is the excessive computational effort associated with contemporary evolutionary optimization algorithms. On the other hand, it is generally perceived that the obtained final designs using conventional optimization algorithms may not necessarily be favored in practice if certain provisions are not stipulated by the algorithm to preclude an abundance of distinct steel section sizes in the final design. Hence, instead of offering a single optimum or near optimum design, it would be more desirable to provide the designer or decision maker with a Pareto front set of non-dominated design alternatives taking into account both the minimum weight as well as the assortment of available steel section sizes in the final design. Accordingly, in this paper, a computationally efficient multi-stage guided stochastic search algorithm is proposed for optimization and standardization of realsize free-form steel double-layer grids. A gradual design-oriented section elimination approach is followed where in the first optimization stage, a complete set of commercially available steel sections is introduced to the algorithm and in the succeeding stages, the size of section list is reduced by eliminating the redundant sizes. Two variants of the algorithm are employed to demonstrate the usefulness of the proposed technique in challenging test examples of free-form steel double-layer grids, and the obtained Pareto fronts are plotted to illustrate the trade-off between minimum weight and assortment of steel section sizes in the final design.Article Citation - WoS: 29Citation - Scopus: 34A Transformative Solution for Construction Safety: Blockchain-Based System for Accident Information Management(Elsevier, 2023) Ahmadisheykhsarmast, Salar; Aminbakhsh, Saman; Sonmez, Rifat; Uysal, FurkanEffective management of accident information is a crucial component of safety management within the construction industry, as it reflects the safety performance of the company and allows them to identify the root causes of accidents and prevent similar accidents in the future. However, existing safety information systems provide self-owned, isolated, and centralized environments and fail to present a secure, transparent, and trustworthy platform for monitoring and management of accident information. To address these issues, this paper presents a novel decentralized blockchain-based system for accident/incident information management of construction projects. The proposed system leverages the benefits and advantages of blockchain, smart contracts, and decentralized IPFS storage to address the security transparency, tampering, and trustworthiness issues of the conventional approaches. The proposed system is simulated by using real-world construction accident data to demonstrate how blockchain technology can provide a novel solution to assure security, transparency, authenticity, availability, and immutability of the accident/incident data for improving safety management.Article Citation - WoS: 10Citation - Scopus: 11E-Constraint Guided Stochastic Search With Successive Seeding for Multi-Objective Optimization of Large-Scale Steel Double-Layer Grids(Elsevier, 2022) Azad, Saeid Kazemzadeh; Aminbakhsh, SamanThis 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.
