Simulation-based Optimization

With growing number of applications relying on complex simulations in areas ranging from science to engineering design, there is a need for algorithms and software implementations that can effectively optimize simulation output with minimal computational efforts. Our work in this context has two aspects: We develop algorithms that rely solely on simulation output. This class of algorithms is called derivative-free optimization algorithms. We investigate computationally attractive yet accurate surrogate models to represent these simulations that drive efficient derivative-free optimization. Because of complex interactions between entities in a supply chain, optimal decision making in a supply

Economic Analysis on Continuous Biopharmaceutical Process

Economic analysis can provide preliminary cost assessment for industrial process at the design stage. In recent years, continuous biopharmaceutical process has become increasingly popular due to its advantages in flexibility, product quality, productivity, and profitability compared to traditional batch process. However, the continuous process is inherently more complex and the associated process design is yet far from mature. Therefore, our study applies economic analysis to the continuous biopharmaceutical process and aims to guide the selection between batch and continuous processes industrially.

Hybrid Modeling Approaches for Pharmaceutical Unit Operations

Multiple modeling approaches exist and continue to advance in the field of pharmaceutical manufacturing that resulted from the need to shift to continuous processing. While there are pros and cons for the various modeling methodologies, we strive to develop hybrid approaches that utilize their strengths and thus promote the usability of these tools for dynamic prediction and optimization purposes. Read more.

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