North Dakota State University

The Optimization and Simulation Laboratory (OSL) is the new research facility housed in the CCMSA, formerly CQRME. This lab is essential to serving the main purpose of the center to develop excellent research at NDSU in the area of computational modeling and simulation of engineering systems supporting the growing industries in North Dakota and to promote computational modeling and simulation education in the state and nation. The OSL is also vital to accomplishing the CCMSA’s vision to build capabilities in the area of computational modeling and simulation in the College of Engineering to serve growing industry needs.The OSL focuses on conducting collaborative and applied research projects on complex industrially relevant engineering problems in various domains such as engineering, management, healthcare, supply chains and logistics, developing and implementing efficient algorithms, optimization, and simulation models that optimize and improve various systems and processes, as well as undertaking educational programs.Researchers and students working in the OSL collaborate with industry partners to apply the developed techniques and solutions to real-world problems. The OSL also provides training and education to students and professionals, helping them to understand and apply optimization and simulation techniques in their respective fields.

The OSL is to be equipped with advanced hardware resources and software tools to conduct collaborative and applied research projects. The lab typically provides CCMSA researchers and students with the following resources:

• a number of high-performance computers specifically configured for scientific large-scale computational optimization and simulation. These computers are usually equipped with advanced hardware, such as multi-core processors and ample storage space;
• a wide range of optimization and simulation software tools and libraries. This includes commercial software packages and solvers, such as GAMS, AMPL, CPLEX, Arena, Flexsim, Simio, Simscale as well as open-source tools like R, Python;
• a library of commonly used simulation models, and optimization algorithms and techniques. This may include linear programming, integer programming, nonlinear programming, stochastic optimization, and metaheuristic algorithms;
• pre-built simulation models and platforms for specific application domains. These models may be used to simulate complex systems, such as supply chains, manufacturing processes, transportation networks, or healthcare systems.
• diverse datasets that can be used for testing and benchmarking optimization and simulation models. These datasets may be real-world data collected from various sources or synthetic data generated using simulation models;
• additionally, the OSL may add specialized equipment or devices for conducting simulations or experiments, depending on the specific focus of the applied research projects.