Aminbakhsh, Saman

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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
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output

8

Articles

7

Citation Count

50

Supervised Theses

1

Scholarly Output Search Results

Now showing 1 - 8 of 8
  • Master Thesis
    Irak'ta Petrol ve Gaz İşleme Tesisleri için İnşaat Projelerinin Risk Değerlendirmesi
    (2021) Dawood, Muhanned Samır Dawood; Aminbakhsh, Saman; Aminbakhsh, Saman; Civil Engineering
    Petrol ve gaz, en önemli ekonomik kaynaklardan biridir ve Irak'taki doğal rezervlerin ana arteri olarak kabul edilmektedir. Bu tür rezervlerle ilişkili işleme tesislerinin inşasında yer alan şirketler ve kurumlar, küresel ekonomide çok önemli bir role sahiptir. Öte yandan, Irak'ın sermaye bütçesi büyük ölçüde petrolun gelirlerinin oranına bağlıdır. Bu bağlamda, birçok araştırmacı, petrol ve gaz işleme tesisleri ile ilgili olan inşaat projeleri ile ilgili riskleri belirlemeye ve analiz etmeye çalışmış zaman, maliyet ve kalite gibi kritik başarı faktörleri üzerindeki etkilerin ortadan kaldirmal için çeşitli yöntemler ve pratik planlar önermişlerdir. Bu çalışmanın amacı, Irak'ın petrol ve gaz sektöründeki inşaat projelerinin ana hedefleri arasında istenen dengeyi tehdit eden risklerin benzer şekilde belirlenmesidir. Bu amaç için, literatür taramasının bulguları, akademik çevrelerden, profesyonellerden ve karar alma otoritelerinden ampirik veriler toplamak için bilimsel alanda yaygın olarak atıfta bulunulan 70 risk öğesini içeren çevrimiçi bir anket geliştirmek için kullanılır. Katılımcılar, Irak'ın Petrol Bakanlığı, Kuveyt Enerji, Bağdat Üniversitesi, Kerbala ve Al-Dorra rafinerileri gibi farklı devletin kurumları ve sivil toplumun kuruluşları ve / veya şirketlerinden seçilir. 143 uzman ve risk derecelendirmelerine ilişkin genel bilgiler beşli Likert ölçeği kullanılarak derlenmiştir. Sekiz risk kategorisi altında gruplandırılarak, risk faktörlerinin her biri için olasılık düzeyi ve etki belirlenir. Yanıt verenlerden toplanan verilere dayanarak, tanımlanan riskleri değerlendirmek ve sıralamak için risk matrisleri geliştirilir; bununla birlikte, ilişkili risk yanıtları burada en yüksek on faktör için önerilmektedir. Toplanan yanıtların istatistiksel analizi için SPSS ve Microsoft Excel programları kullanılmış ve verilerin tutarlılığı Cronbach's Alpha güvenirlik katsayısı kullanılarak doğrulanmıştır. Sonuçlar, projelerin başarısını dolaylı olarak etkileyebilecek en önemli risk unsurlarının, 'Küresel petrol ve gaz fiyatlarında istikrarsızlık' ve 'işgücüne yapılan ödemelerde gecikme' olduğuna işaret ediyor.
  • Article
    Citation Count: 0
    Resource Allocation Capabilities of Commercial Project Management Software Packages for Resource Leveling and Resource Constrained Project Scheduling Problems: a Comparative Study
    (2023) Albayati, Noor; Aminbakhsh, Saman; Aminbakhsh, Saman; Civil Engineering
    In 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 Count: 9
    Multi-Stage Guided Stochastic Search for Optimization and Standardization of Free-Form Steel Double-Layer Grids
    (Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Aminbakhsh, Saman; Shaban, Samer S. S.; Azad, Saeıd Kazemzadeh; Civil Engineering; Department of Civil Engineering
    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 Count: 4
    A Transformative Solution for Construction Safety: Blockchain-Based System for Accident Information Management
    (Elsevier, 2023) Ahmadisheykhsarmast, Salar; Aminbakhsh, Saman; Aminbakhsh, Saman; Sonmez, Rifat; Uysal, Furkan; Civil Engineering
    Effective 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 Count: 18
    High-Dimensional Optimization of Large-Scale Steel Truss Structures Using Guided Stochastic Search
    (Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Aminbakhsh, Saman; Azad, Saeıd Kazemzadeh; Civil Engineering; Department of Civil Engineering
    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.
  • Article
    Citation Count: 0
    Optimizing Three-Dimensional Trade-Off Problem of Time-Cost Over Multi-Mode Projects With Generalized Logic
    (Mdpi, 2024) Aminbakhsh, Saman; Aminbakhsh, Saman; Abdulsattar, Abdulrahman M.; Civil Engineering
    Clients typically tend to aim for reasonable prices, minimum possible makespans, and the best quality for the construction projects that they engage in. Evidently, weighing the available offers and coming up with an optimal decision can pose challenges for the decision makers. In this regard, the generation of a tool that helps decision makers strike a proper balance among the conflicting project objectives (i.e., time, cost, and quality) is imperative. To this end, this study proposes a method which assists in the selection of the best compromise choices among the options available for each of the project activities. In addition to the time and cost, the proposed method is designed to bring the quality aspect into the equation as well. To quantify the quality, a value referring to the weighted importance and performance of each activity is used. The proposed method is based on a modified multi-objective genetic algorithm (GA) that incorporates the domination concept for the selection of the best solutions out of the potential candidates. The GA-based method is capable of handling an unlimited number of precedence relationships for each activity, and above all, it is able to capture and unravel any type of logical relationship. This very feature significantly improves the practical relevance of this research, as the parallelization of activities is a common practice in real-life projects. Planners benefit from the various types of relationships (i.e., Start to Start, Start to Finish, Finish to Start, and Finish to Finish), and the concept of lag time frequently introduces parallelization into the network. Overlapped activities, in turn, help reduce the unwanted idle times and speed up the project significantly. Accordingly, in order to demonstrate the application and effectiveness of the proposed model, it has been used in the solution of four time-cost-quality (TCQ) trade-off problems, three of which are generated within the context of this paper. The practiced instances include a small benchmark TCQT problem with 18 activities taken from the literature in addition to more complex 29- and 63-activity TCQTPs produced herein based on benchmark time-cost trade-off problems. The performance of the presented approach is ultimately examined over a large-scale, real-case construction project with over four hundred activities and generalized logic in an unprecedented attempt to validate a model in the realm of TCQTPs. The successful results of the experiments reveal the effectiveness of the proposed model and corroborate the feasibility of its application by the planners amidst arduous decision-making processes.
  • Article
    Citation Count: 14
    Activity Uncrashing Heuristic With Noncritical Activity Rescheduling Method for the Discrete Time-Cost Trade-Off Problem
    (Asce-amer Soc Civil Engineers, 2020) Sonmez, Rifat; Aminbakhsh, Saman; Aminbakhsh, Saman; Atan, Tankut; Civil Engineering
    Despite intensive research efforts that have been devoted to discrete time-cost optimization of construction projects, the current methods have very limited capabilities for solving the problem for real-life-sized projects. This study presents a new activity uncrashing heuristic with noncritical activity rescheduling method to narrow the gap between the research and practice for time-cost optimization. The uncrashing heuristic searches for new solutions by uncrashing the critical activities with the highest cost-slope. This novel feature of the proposed heuristic enables identification and elimination of the dominated solutions during the search procedure. Hence, the heuristic can determine new high-quality solutions based on the nondominated solutions. Furthermore, the proposed noncritical activity rescheduling method of the heuristic decreases the amount of scheduling calculations, and high-quality solutions are achieved within a short CPU time. Results of the computational experiments reveal that the new heuristic outperforms state-of-the-art methods significantly for large-scale single-objective cost minimization and Pareto front optimization problems. Hence, the primary contribution of the paper is a new heuristic method that can successfully achieve high-quality solutions for large-scale discrete time-cost optimization problems.
  • Article
    Citation Count: 5
    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; Aminbakhsh, Saman; Azad, Saeıd Kazemzadeh; Civil Engineering; Department of Civil Engineering
    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.