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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.Article Simultaneous Pickup and Delivery Model Suggestion for Personnel Transportation in Covid-19 Pandemic Conditions(Wroclaw Univ Science & Technology, Fac Management, 2023) Kose, Erkan; Vural, Danışment; Kokmazer, Ahsen; Vural, Danisment; Gokceoglu, Gokce Gul; Savli, Pinar; Vural, Danışment; Industrial Engineering; Industrial EngineeringThe impact of COVID-19 on the transportation costs of a large-scale company has been examined. Before the pandemic, shift personnel were transported to the factory by shuttles, and after a quick shift change, other shift personnel were transported back to their homes. However, with the implementation of laws mandating the reduction of shuttle seat capacities, transportation costs have risen significantly. To address this issue, a new simultaneous pickup and delivery model is proposed as an alternative to the separate transportation of shift workers. The results of this study indicate that the proposed model provides a substantial advantage in terms of both the number of vehicles used and the total distance traveled, leading to a significant reduction in costs. This research underscores the importance of effective operations research practices for the profitability of companies, particularly in extraordinary circumstances such as the COVID-19 pandemic.Article Citation - Scopus: 1Optimizing the Stochastic Deployment of Small Base Stations in an Interleave Division Multiple Access-Based Heterogeneous Cellular Networks(Wiley, 2022) Noma-Osaghae, Etinosa; Misra, Sanjay; Koyuncu, MuratThe use of small base stations (SBSs) to improve the throughput of cellular networks gave rise to the advent of heterogeneous cellular networks (HCNs). Still, the interleave division multiple access (IDMA) performance in sleep mode active HCNs has not been studied in the existing literature. This research examines the 24-h throughput, spectral efficiency (SE), and energy efficiency (EE) of an IDMA-based HCN and compares the result with orthogonal frequency division multiple access (OFDMA). An energy-spectral-efficiency (ESE) model of a two-tier HCN was developed. A weighted sum modified particle swarm optimization (PSO) algorithm simultaneously maximized the SE and EE of the IDMA-based HCN. The result obtained showed that the IDMA performs at least 68% better than the OFDMA on the throughput metric. The result also showed that the particle swarm optimization algorithm produced the Pareto optimal front at moderate traffic levels for all varied network parameters of SINR threshold, SBS density, and sleep mode technique. The IDMA-based HCN can improve the throughput, SE, and EE via sleep mode techniques. Still, the combination of network parameters that simultaneously maximize the SE and EE is interference limited. In sleep mode, the performance of the HCN is better if the SBSs can adapt to spatial and temporal variations in network traffic.Article Citation - WoS: 2Citation - Scopus: 4Optimum Cost Prediction of Reinforced Concrete Cantilever Retaining Walls(Mdpi, 2023) Akis, EbruReinforced concrete cantilever retaining walls (RCCRWs) are widely used in civil engineering projects as a common type of retaining structure. The design of these structures focuses on ensuring safety against various failure scenarios and compliance with standard building code requirements. This research aims to enhance the design process of RCCRWs by developing a specific code and optimizing it through a metaheuristic-based algorithm. In this study, the cost prediction of RCCRWs is also investigated through a parametric study involving key variables such as wall height, seismic zone, backfill material properties, and backfill inclination angle. To achieve this, non-linear regression analysis is employed to establish an empirical correlation, enabling cost estimation for optimized RCCRWs. The resulting prediction equation is simple to use, requiring only limited inputs. Therefore, it can be applied during the initial stages of a project, making a valuable contribution in determining approximate costs for RCCRW projects.
