Welcome to the home page of Professor Andrew Allman’s Process Systems Research Team at the University of Michigan’s Department of Chemical Engineering. Our team focuses on developing theory and algorithms to support optimal decision making for the economic, safe, and sustainable design, operation, and control of next generation chemical, energy, and biochemical production systems. Our work is highly interdisciplinary and we are always seeking new collaborations and novel applications of our optimization tools.

Recent Team News

Jan. 2023 – Our work on analysis of optimal model predictive control in numbered-up modular systems is accepted for publication in Digital Chemical Engineering. (Link)
Jan. 2023 – The team travels to the 2023 FOCAPO/CPC conference in San Antonio. Andrew talks about dynamic changes in objective correlation for many objective operation and control, while Yi presents a poster on dynamically reconfiguring numbered-up modular systems.
Jan. 2023 – Andrew receives the NSF CAREER award for $559K. We are extremely honored to be selected for this award and are excited to use it to further our work on many-objective optimization for sustainable decision making.
Nov. 2022 – Our work on systematic dimensionality reduction for many objective mixed integer linear optimization in sustainable process systems is accepted for publication in AIChE Journal. (Link)
Nov. 2022 – The team travels to the 2022 AIChE Annual Meeting in Phoenix. Andrew presents our work on dimensionality reduction in many-objective optimization, while Yi presents on symmetry in the control of numbered-up modular systems.
Oct. 2022 – Andrew receives the ACS-PRF Doctoral New Investigator award for $110K. We are excited to be able to use this to continue our work analyzing the dynamics of numbered-up modular systems, exploring applications to shale gas upgrading.
Oct. 2022 – Hongxuan Wang joins our team as a first year ChE Ph.D. student. He will be working on developing machine learning tools to identify most efficient optimization solution methods. Welcome Hongxuan!
July 2022 – Justin leaves the group to begin an engineering position with Dow Chemical. Best of luck, Justin!
July 2022 – Andrew gives a virtual seminar on many-objective optimization for real-time operation and control at Imperial College London.
June 2022 – Andrew gives talks on operation of numbered-up modular systems at AMPC 2022, and on dimensionality reduction in many objective optimization at ACC 2022.
Mar. 2022 – Our work on distributed, fairness guided optimization for the operation of process networks is accepted for publication in Computers and Chemical Engineering. (Link)
Nov. 2021 – Andrew presented our work on distributed, fairness guided optimization for the operation of process networks at the 2021 AIChE annual meeting.
Oct. 2021 – Yi successfully passes her Thesis Proposal Exam. Congrats Yi!
July 2021 – Andrew, as part of a research team with Michigan ChE Profs. Nina Lin (lead PI) and Maciek Antoniewicz, is awarded a $1.5M DOE grant for “Developing, understanding, and harnessing modular carbon/nitrogen-fixing tripartite microbial consortia for versatile production of biofuel and platform chemicals.” DOE press release
May 2021 – Justin successfully passes his Doctoral Candidacy Exam. Congrats Justin!
May 2021 – Our work on developing a branch-and-price algorithm for a class of nonconvex mixed integer nonlinear programs is accepted for publication in the Journal of Global Optimization. Link
Apr. 2021 – Our work on modular and mobile production units for biomass waste-to-energy applications is accepted for publication in Computers and Chemical Engineering. Link
Mar. 2021 – Andrew (virtually) presents our work on the community-based decomposition of optimization problems as a seminar to the University of Michigan controls group. Link to video