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
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
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…