MATERIAL COST OPTIMIZATION OF ONE-WAY REINFORCED CONCRETE SLABS USING AN ELITIST GENETIC ALGORITHM: A SENSITIVITY ANALYSIS BASED ON ACI ۳۱۸-۱۹

This study uses an elitist Genetic Algorithm (GA) to optimize material costs in one-way reinforced concrete slabs, adhering to ACI ۳۱۸-۱۹. A sensitivity analysis demonstrated the critical role of elitism in GA performance. Without elitism, the GA consistently failed to reach the target objective, with success rates often nearing zero across various crossover fractions. Incorporating elitism dramatically increased success rates, highlighting the importance of preserving high-performing individuals. With an optimal configuration of ۰.۳ crossover fraction and ۰.۴۵ elite percentage, a ۹۲% success rate was achieved, finding a cost of ۲۴.۹۱ in ۴۶ of ۵۰ runs for a simply supported slab. This optimized design, compared to designs based on ACI ۳۱۸-۹۹ and ACI ۳۱۸-۰۸, yielded material cost savings of between ۵.۸% to ۸.۶% for simply supported, one-end continuous, both-ends continuous, and cantilevered slabs. The influence of slab dimensions on cost was evaluated across ۶۴ scenarios, varying slab lengths from ۵ to ۲۰ feet for each support condition. Resulting cost versus slab length diagrams illustrate the economic benefits of GA optimization.

کلیدواژه ها:

Optimal design ، Structural optimization ، Reinforced Concrete Slabs ، Genetic Algorithm ، ACI ۳۱۸-۱۹ ، Elite Percentage ، Sensitivity Analysis