en Applications Applications پژوهشي Research <span style="font-size:11pt"><span style="text-justify:kashida"><span style="text-kashida:0%"><span style="line-height:normal"><span style="font-family:Calibri,sans-serif"><span lang="EN-GB" style="font-size:11.5pt"><span new="" roman="" style="font-family:" times="">This study uses an elitist Genetic Algorithm (GA) to optimize material costs in one-way reinforced concrete slabs, adhering to ACI 318-19. 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 0.3 crossover fraction and 0.45 elite percentage, a 92% success rate was achieved, finding a cost of 24.91 in 46 of 50 runs for a simply supported slab. This optimized design, compared to designs based on ACI 318-99 and ACI 318-08, yielded material cost savings of between 5.8% to 8.6% for simply supported, one-end continuous, both-ends continuous, and cantilevered slabs. The influence of slab dimensions on cost was evaluated across 64 scenarios, varying slab lengths from 5 to 20 feet for each support condition. Resulting cost versus slab length diagrams illustrate the economic benefits of GA optimization.</span></span></span></span></span></span></span> Optimal design, Structural optimization, Reinforced Concrete Slabs, Genetic Algorithm, ACI 318-19, Elite Percentage, Sensitivity Analysis 573 593 http://ijoce.iust.ac.ir/browse.php?a_code=A-10-6463-12&slc_lang=en&sid=1 B. Ahmadi-Nedushan behrooz.ahmadi@yazd.ac.ir 180031947532846002545 180031947532846002545 Yes Department of Civil Engineering, Yazd University, Yazd, Iran A. M. Almaleeh 180031947532846002546 180031947532846002546 No Department of Civil Engineering, Yazd University, Yazd, Iran