6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.NE2024
Memory-Driven Metaheuristics: Improving Optimization Performance
Salar Farahmand-Tabar
Metaheuristics are stochastic optimization algorithms that mimic natural processes to find optimal solutions to complex problems. The success of metaheuristics largely depends on t…
cs.NE2024★ 1 cited
Bilinear Fuzzy Genetic Algorithm and Its Application on the Optimum Design of Steel Structures with Semi-rigid Connections
Salar Farahmand-Tabar, Payam Ashtari
An improved bilinear fuzzy genetic algorithm (BFGA) is introduced in this chapter for the design optimization of steel structures with semi-rigid connections. Semi-rigid connection…
cs.NE2024★ 6 cited
Boosting the Efficiency of Metaheuristics Through Opposition-Based Learning in Optimum Locating of Control Systems in Tall Buildings
Salar Farahmand-Tabar, Sina Shirgir
Opposition-based learning (OBL) is an effective approach to improve the performance of metaheuristic optimization algorithms, which are commonly used for solving complex engineerin…