A tribute to an advisor, a mentor and a friend

Transcription

1 A tribute to an advisor, a mentor and a friend Marianthi Ierapetritou Department of Chemical and Biochemical Engineering Laboratory for Optimization and Systems Analysis 1

2 Two years : Four projects: Planning under Uncertainty Chris as an advisor Protein Folding and Peptide Docking using Global Optimization Short-term scheduling using continuous time representation Optimal Location allocation problem Application to oil well location Twelve publications 2

3 Chris as an advisor: Floudas, C.A., Z. Gumus, and M.G. Ierapetritou. Global Optimization for the Feasibility Test and Flexibility Index Problems.,Ind. & Eng. Chem. Res, 40(2), , Ierapetritou M.G., I.P. Androulakis, D.S. Monos and C.A. Floudas. Structure Prediction of Binding Sites of MHC Class II Molecules based on the Crystal of HLA-DR1 and Global Optimization, State of the Art in Global Optimization: Computational Methods and Applications, Eds: C.A. Floudas and P.M. Pardalos, Kluwer, , Ierapetritou M.G., T.S. Hene and C.A. Floudas. Effective Continuous-Time Formulation for Short-Term Scheduling: III Multiple Intermediate Due Dates Ind. & Eng. Chem, 38(9), Ierapetritou M.G., and C.A. Floudas and S. Vansantharajan and A.S. Gullick, A Decomposition Based Approach for Optimal Location of Vertical Wells AIChE J., 45(4), , Ierapetritou M.G., and C.A. Floudas. Effective Continuous-Time Formulation for Short- Term Scheduling: I. Multipurpose Batch Processes Ind. & Eng. Chem. Res., 37(11), , Ierapetritou M.G., and C.A. Floudas. Effective Continuous-Time Formulation for Short- Term Scheduling: II. Multipurpose/Multiproduct Continuous Processes Ind. & Eng. Chem. Res., 37(11), , Ierapetritou, M.G, and C.A. Floudas. Short-Term Scheduling: New Mathematical Models vs Algorithmic Improvements. Comp. & Chem. Eng., 22(S1), S419-S426,

4 Chris as an advisor: Klepeis, J.L., M.G. Ierapetritou, and C.A. Floudas. Protein Folding and Peptide Docking: A Molecular Modeling and Global Optimization Approach. Comp. & Chem. Eng., 22(S1), S3-S10, Klepeis, J.L., I.P. Androulakis, M.G. Ierapetritou, and C.A. Floudas. Predicting Solvated Peptide Conformations via Global Minimization of Energetic atom-to-atom Interactions. Comp. & Chem. Eng.,22(6), , Androulakis I.P., N.N. Nayak, M.G. Ierapetritou, D.S. Monos and C.A. Floudas, Identification of Peptide Binding Specificity for Pocket 1 of HLA-DR1 Based on Global Minimization of Energy Interactions. Proteins: Structure,Function and Genetics, 29(1), , Ierapetritou, M.G., E.N. Pistikopoulos and C. A. Floudas, Operational Planning Under Uncertainty. Comp. & Chem. Eng., 20, , Visweswaran V., Floudas C.A., Ierapetritou, M.G. and Pistikopoulos E.N., A Decomposition Based Global Optimization Approach for Bi- Level Convex Programming Problems. State of the Art in Global Optimization: Computational Methods and Applications C.A. Floudas and P.M. Pardalos (eds), Springer, pages: ,

5 Chris as a mentor Always push the boundaries Work on the scheduling problem 5

6 Continuous Formulation of Short-term Scheduling Ierapetritou M.G., and C.A. Floudas. Effective Continuous-Time Formulation for Short-Term Scheduling: I. Multipurpose Batch Processes Ind. & Eng. Chem. Res., 37(11), , citations - Initiated a huge level of activity in this area! The basic idea of the proposed formulation is that it decouples the task events (i) from the unit events (j). This is achieved by the consideration of different variables to represent the task events (i.e., the beginning of the task), denoted as wv(i,n), and the unit events (i.e., the beginning of unit utilization), denoted as yv(j,n), as shown in the Figure. If task event i starts at event point n, then wv(i,n) = 1; otherwise, it is zero. If unit event j takes place at event point n, then yv(j,n) = 1; otherwise, it is zero. This results in fewer binary variables and small integrality gaps. 6

7 Process Scheduling other publications for Chris lab Floudas, C.A., and Lin, X.X. Continuous-time versus discrete-time approaches for scheduling of chemical processes: a review Comp. Chem. Eng., 28(11), , citations Great Review of the scheduling work Ierapetritou M.G., and C.A. Floudas. Effective Continuous-Time Formulation for Short-Term Scheduling: II. Continuous and semi-continuous processes Ind. & Eng. Chem. Res., 37(11), , citations Extension of the original work to cover continuous processes Lin, X.X., Janak, S.L., and C.A. Floudas. A new robust optimization approach for scheduling under uncertainty: I. Bounded uncertainty Comp. Chem. Eng., 28(6-7), , citations Pioneer work in the area of robust scheduling Janak, S.L., Lin, X.X., and C.A. Floudas. Enhanced continuous-time unit-specific event-based formulation for short-term scheduling of multipurpose batch processes: Resource constraints and mixed storage policies Ind. & Eng. Chem. Res., 43(10), , citations Smart way to incorporate realistic storage constraints and many more 7

8 Chris as a mentor Be persistent never give up Work on the protein folding problem 8

9 Protein Docking Problem Docking problem formulated as a non-convex optimization problem Use deterministic global optimum method (abb) to solve it. Based on converging upper and lower bounds Upper bound : local solution of the nonconvex problem Lower bound: convex lower bounding problem which is constructed based on eigenvalue analysis of the nonconvex potential 9

10 Chris as a mentor Work on your strengths Planning under uncertainty 10

11 Planning under Uncertainty Ierapetritou M.G., E.N. Pistikopoulos, and C.A. Floudas. Operational Planning Under Uncertainty Comp. Chem. Eng., 12(12), , 1996.! VI(x 1,θ) = F1(θ) F2(x 1,θ) F1 : wait-and-see; F2: Here-and-now Quantify the value of information in the face of uncertainty 11

12 Chris as a mentor Embrace new challenges Facility location problem 12

13 Optimal Location of Wells Ierapetritou M.G., and C.A. Floudas and S. Vansantharajan and A.S. Gullick, A Decomposition Based Approach for Optimal Location of Vertical Wells AIChE J., 45(4), , Novel decomposition-based approach to address the problem of field development for a given reservoir: Reservoir characterization Field decomposition Iterative methodology Efficient MILP problem formulation 13

14 Chris as a dear friend 14

15 Following his advice 15

16 Main Research Areas Pharma Biomass conversion M M V i = ωv screw Modeling Sensitivity and Feasibility Analysis m i V = V i ρ B Optimization of Process Operations Incorporation of uncertainty Process Control Integrated Decision Making 16

17 Chapter 4 : The people: My former PhD students Previous Ph.D. Students Clockwise: Nihar Sahay, Zhaojia Lin, Jinjun Zhuge, Nikisha Shah, Fani Boukovala, Amanda Rogers, Berverly Smith, Mehmet Orman, Vijie Gao, Shuliang Zhang, Nripen Sharma, From left to right: Kaiyuan He, Zukui Li, Hong Yang, Eddie Davis, Patricia Brieva From left to right: Aditya Bindal, Zhenya Jia, Daniel Wu, Ipsita Banerjee, Vishal Goyal 17

18 Laboratory for Optimization and Systems Analysis From Left :, Zilong Wang, Shu Yang, Shishir Vadadodaria, Ravendra Singh, Praneeth Annam, Abhay Athaley,, Nirupa Metta, Parham Farzan, Lisia Diaz, Sebastian Escotet, Marianthi Ierapetritou, Charles Foster 18

19 Thanks 19