Investigate the Applicability of Gray Wolf Optimization Algorithm in Determining the Optimal Dimensions of Concrete Dams

Acquiring optimal dimensions of concrete dams by reducing the cross section will reduce the volume of concrete used and consequently reduce construction costs. Due to multiplicity of constraints which leads to complexity of the decision space, meta-heuristic optimization algorithms have been increasingly used in optimal design of gravity dams. In this study, performance of Grey Wolf Optimizer was assessed in optimal design of Koyna concrete gravity dam and the results were compared to Particle Swarm Optimization. Results indicated that Grey Wolf Optimization was able to reach to a 5.2 percent lower mean optimal cost over 10 runs result with considerably a 61.5 percent smaller number of function evaluations compared to Particle Swarm Optimization and considering stability of the algorithm results obtained from Grey Wolf Optimization had smaller standard deviation than Particle Swarm Optimization. However, in 10 consecutive runs, the minimum optimal value reached using Particle Swarm Optimization was 1.6% smaller than the smallest optimal value obtained from Grey Wolf Optimization, considering overall performance of algorithms, Grey Wolf Optimization presented a promising performance having a faster and stable convergence