PARALLEL ALGORITHMS FOR NONLINEAR PROGRAMMING AND APPLICATIONS IN PHARMACEUTICAL MANUFACTURING

Effective manufacturing of pharmaceuticals presents a number of challenging optimization problems due to complex distributed, time-independent models and the need to handle uncertainty. These challenges are multiplied when real-time solutions are required. The demand for fast solution of nonlinear optimization problems, coupled with the emergence of new concurrent computing architectures, drives the need for parallel algorithms to solve challenging NLP problems. The goal of this work is the development of parallel algorithms for nonlinear programming problems on different computing architectures, and the application of large-scale nonlinear programming on challenging problems in pharmaceutical manufacturing.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Chemical Engineering

Year

2015

Author dc:creator

• Cao, Yankai

Contributors dc:contributor

• Carl Laird
• Zoltan Nagy
• Gintaras Reklaitis
• Andrew Liu

Repository record dc:identifier

https://docs.lib.purdue.edu/open_access_dissertations/1098

OAI identifier oai:identifier

oai:docs.lib.purdue.edu:open_access_dissertations-2314