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Article Algorithm-Driven Placement Optimization of Aircraft-Mounted VHF Antennas for Mutual Coupling Reduction(MDPI, 2026) Hakanoglu, Baris Gurcan; Dalveren, Yaser; Oz, Emre; Kara, Ali; Derawi, MohammadThis study investigates algorithm-driven placement optimization of two aircraft-mounted VHF monopole antennas to mitigate mutual coupling under realistic installation constraints. A parameterized 3D aircraft model inspired by general-aviation platforms is analyzed using full-wave electromagnetic simulations over the 30-100 MHz band. The optimization problem is formulated to reduce inter-antenna coupling across the operating band while restricting the search space to physically installable regions on the airframe. Two global optimization methods, Genetic Algorithm and Particle Swarm Optimization, are applied and compared under the identical constraints and objective definitions. The results show that both optimizers achieve a significant reduction in coupling relative to non-optimized placements, with comparable overall performance. Installed far-field radiation characteristics are further evaluated to verify that the optimized solutions preserve, and in some cases improve, the omnidirectional coverage required for airborne VHF communication. The proposed workflow provides a practical, simulation-driven framework for electromagnetic compatibility (EMC)-oriented antenna integration on complex aircraft platforms.Article Citation - WoS: 3Citation - Scopus: 7Optimization-Based Scheduling of Construction Projects With Generalized Precedence Relationships: a Real-Life Case Study(Sharif University of Technology, 2024) Aminbakhsha, S.; Ahmed, A.; Aminbakhsh, SamanConcomitant reduction of cost and duration is recognized as one of the main aspects of construction planning. Expedition of project schedule naturally incurs extra costs due to implementation of more productive and/or high-price construction techniques. Meanwhile, a reduction in time is usually plausible only down to a certain limit, below which renders expeditions either technically or nancially unviable. Thus, striking a reasonable balance between project cost and duration remains a desirable yet challenging task for which there has been a myriad of advancements and literature. Despite the many studies associated with this problem-referred to as Time-Cost Trade-off Problem (TCTP) it is observed that only a few exercise TCTPs with the generalized logical relationships. This observation holds despite the fact that generalized precedence relationships are imperative to introduce parallelism and to secure a realistic overlap among the activities. In this regard, a Simulated Annealing-based (SA-based) Genetic Algorithm (GA) as proposed herein, is specically designed to provide the capability of exerting TCTPs with properly overlapped activities. Eciency of this algorithm is tested over a range of problems and its performance is validated over a large-scale real-case construction project. Results of the hybridized GA indicate fast and robust convergence to high-quality solutions. © 2024, Sharif University of Technology. All rights reserved.
