Scope for industrial applications of production scheduling models and solution methods

I Harjunkoski, CT Maravelias, P Bongers… - Computers & Chemical …, 2014 - Elsevier
This paper gives a review on existing scheduling methodologies developed for process
industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling …

Continuous-time versus discrete-time approaches for scheduling of chemical processes: a review

CA Floudas, X Lin - Computers & Chemical Engineering, 2004 - Elsevier
An overview of developments in the scheduling of multiproduct/multipurpose batch and
continuous processes is presented. Existing approaches are classified based on the time …

Network‐constrained unit commitment‐based virtual power plant model in the day‐ahead market according to energy management strategy

S Pirouzi - IET Generation, Transmission & Distribution, 2023 - Wiley Online Library
Energy management of a virtual power plant (VPP) that consists of wind farm (WF), energy
storage systems and a demand response program is discussed in the present study. The …

[HTML][HTML] A deep reinforcement learning approach for chemical production scheduling

CD Hubbs, C Li, NV Sahinidis, IE Grossmann… - Computers & Chemical …, 2020 - Elsevier
This work examines applying deep reinforcement learning to a chemical production
scheduling process to account for uncertainty and achieve online, dynamic scheduling, and …

Dynamic multi-robot task allocation under uncertainty and temporal constraints

S Choudhury, JK Gupta, MJ Kochenderfer, D Sadigh… - Autonomous …, 2022 - Springer
We consider the problem of dynamically allocating tasks to multiple agents under time
window constraints and task completion uncertainty. Our objective is to minimize the number …

[HTML][HTML] A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

J Scott, W Ho, PK Dey, S Talluri - International Journal of Production …, 2015 - Elsevier
Integrated supplier selection and order allocation is an important decision for both designing
and operating supply chains. This decision is often influenced by the concerned …

On the road between robust optimization and the scenario approach for chance constrained optimization problems

K Margellos, P Goulart, J Lygeros - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
We propose a new method for solving chance constrained optimization problems that lies
between robust optimization and scenario-based methods. Our method does not require …

A comparative theoretical and computational study on robust counterpart optimization: I. Robust linear optimization and robust mixed integer linear optimization

Z Li, R Ding, CA Floudas - Industrial & engineering chemistry …, 2011 - ACS Publications
Robust counterpart optimization techniques for linear optimization and mixed integer linear
optimization problems are studied in this paper. Different uncertainty sets, including those …

[HTML][HTML] Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting

M Norouzi, J Aghaei, T Niknam, M Alipour, S Pirouzi… - Applied Energy, 2023 - Elsevier
The future of energy flexibility in microgrids (MGs) is steering towards a highly granular
control of the end-user customers. This calls for more highly accurate uncertainty forecasting …

Recent advances in mathematical programming techniques for the optimization of process systems under uncertainty

IE Grossmann, RM Apap, BA Calfa… - Computers & Chemical …, 2016 - Elsevier
Optimization under uncertainty has been an active area of research for many years.
However, its application in Process Systems Engineering has faced a number of important …