7 results
Search Results
Now showing 1 - 7 of 7
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: 24Activity 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; Atan, TankutDespite 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 - 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: 11Citation - Scopus: 12E-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.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.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.
