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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 - 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: 2Citation - Scopus: 2Optimizing Three-Dimensional Trade-Off Problem of Time-Cost Over Multi-Mode Projects With Generalized Logic(Mdpi, 2024) Aminbakhsh, Saman; Abdulsattar, Abdulrahman M.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.
