1 - 2 |
Editorial of FOCAPO/CPC 2017 Preface Maravelias CT, Megan L, Wassick JM, Ydstie BE |
3 - 13 |
Advanced optimization strategies for integrated dynamic process operations Biegler LT |
14 - 42 |
Expanding scope and computational challenges in process scheduling Castro PM, Grossmann IE, Zhang Q |
43 - 51 |
Decomposing complex plants for distributed control: Perspectives from network theory Daoutidis P, Tang WT, Jogwar SS |
52 - 68 |
Nonsmooth differential-algebraic equations in chemical engineering Stechlinski P, Patrascu M, Barton PI |
69 - 80 |
Dynamic latent variable analytics for process operations and control Dong YN, Qin SJ |
81 - 88 |
A framework for modeling and optimizing dynamic systems under uncertainty Nicholson B, Siirola J |
89 - 98 |
Economic MPC and real-time decision making with application to large-scale HVAC energy systems Rawlings JB, Patel NR, Risbeck MJ, Maravelias CT, Wenzel MJ, Turney RD |
99 - 110 |
Global optimization of grey-box computational systems using surrogate functions and application to highly constrained oil-field operations Beykal B, Boukouvala F, Floudas CA, Sorek N, Zalavadia H, Gildin E |
111 - 121 |
Machine learning: Overview of the recent progresses and implications for the process systems engineering field Lee JH, Shin J, Realff MJ |
122 - 129 |
The impact of digitalization on the future of control and operations Isaksson AJ, Harjunkoski I, Sand G |
130 - 144 |
Smart manufacturing and energy systems Edgar TF, Pistikopoulos EN |
145 - 157 |
A multitree approach for global solution of ACOPF problems using piecewise outer approximations Liu JF, Bynum M, Castillo A, Watson JP, Laird CD |
158 - 170 |
Stochastic model predictive control - how does it work? Heirung TAN, Paulson JA, O'Leary J, Mesbah A |
171 - 190 |
Process operational safety via model predictive control: Recent results and future research directions Albalawi F, Durand H, Christofides PD |
191 - 200 |
Optimizing the Design of New and Existing Supply Chains at Dow AgroSciences Bassett M |
201 - 210 |
On improving the online performance of production scheduling: Application to air separation units Lotero I, Gopalakrishnan A, Roba T |
211 - 220 |
Application of formal verification and falsification to large-scale chemical plant automation systems Rawlings BC, Wassick JM, Ydstie BE |
221 - 224 |
Scheduling, optimization and control of power for industrial cogeneration plants Bindlish R |
225 - 244 |
Framework for a smart data analytics platform towards process monitoring and alarm management Hu WK, Shah SL, Chen TW |
245 - 253 |
Petroleum production optimization - A static or dynamic problem? Foss B, Knudsen BR, Grimstad B |
254 - 264 |
Economic opportunities for industrial systems from frequency regulation markets Dowling AW, Zavala VM |
265 - 272 |
A two-stage procedure for the optimal sizing and placement of grid-level energy storage Adeodu O, Chmielewski DJ |
273 - 280 |
A process systems approach for detailed rail planning and scheduling applications Zyngier D, Lategan J, Furstenberg L |
281 - 295 |
An algorithm for gradient-based dynamic optimization of UV flash processes Ritschel TKS, Capolei A, Gaspar J, Jorgensen JB |
296 - 305 |
On decoupling rate processes in chemical reaction systems - Methods and applications Billeter J, Rodrigues D, Srinivasan S, Amrhein M, Bonvin D |
306 - 317 |
Modeling of hydraulic fracturing and designing of online pumping schedules to achieve uniform proppant concentration in conventional oil reservoirs Siddhamshetty P, Yang S, Kwon JSI |
318 - 324 |
Analysis of the multiplicity of steady-state profiles of two tubular reactor models Dochain D |