PERFORMANCE ANALYSIS OF SIMULATION-BASED MULTIOBJECTIVE OPTIMIZATION USING HIGH PERFORMANCE COMPUTING
Shide Salimi1, Mohammed Mawlana2 and Amin Hammad3
1) M.Sc. Student, Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, Quebec, Canada.
2) Ph.D. Candidate, Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, Quebec, Canada.
3) Prof., Department of Concordia Institute for Information Systems Engineering, Montreal, Quebec, Canada.
Abstract: Conventionally, efforts are made to optimize the performance of simulation models by examining several possible resource combinations. However, the number of possible resource assignments increases exponentially with the increase of the range of available resources. Many researchers combined Genetic Algorithms (GAs) and other optimization techniques with simulation models to reach the Pareto solutions. However, due to the large number of resources required in complex and large-scale construction projects, which results in a very large search space, and the limitation of the GA capability in fast convergence to the optimum results, High Performance Computing (HPC) is required to reduce the computational time. Moreover, the values of the optimization parameters directly affect the performance of the optimization algorithm. Therefore, finding the promising configuration for the optimization method and analyzing the impact of these parameter on the overall performance of a system is another challenge that researchers are facing when working with optimization algorithms. This paper proposes the usage of Non-dominated Sorting Genetic Algorithm (NSGA-) as the optimization engine integrated with Discrete Event Simulation (DES) to model the bridge construction processes. The parallel computing platform is applied to reduce the computation time necessary to deal with multiple objective functions and the large search space. In addition, sensitivity analysis is applied to identify the promising configuration of the GA and to analyze the impact of GA parameters on the overall performance of the specific simulation-based optimization problem.
Keywords: HPC, Simulation, Multi-objective Optimization, Sensitivity Analysis, Bridge Construction Processes.
Shide Salimi, Mohammed Mawlana, and Amin Hammad. “PERFORMANCE ANALYSIS OF SIMULATION-BASED MULTIOBJECTIVE OPTIMIZATION USING HIGH PERFORMANCE COMPUTING.” In Proceedings of International Conference on Civil and Building Engineering Informatics (ICCBEI 2015), 120. Tokyo, Japan, 2015.