Process systems engineering–the generation next?
Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …
and components describing the behavior of a physicochemical system, via mathematical …
A review and comparison of solvers for convex MINLP
In this paper, we present a review of deterministic software for solving convex MINLP
problems as well as a comprehensive comparison of a large selection of commonly …
problems as well as a comprehensive comparison of a large selection of commonly …
Energy-optimized partial computation offloading in mobile-edge computing with genetic simulated-annealing-based particle swarm optimization
Smart mobile devices (SMDs) can meet users' high expectations by executing computational
intensive applications but they only have limited resources, including CPU, memory, battery …
intensive applications but they only have limited resources, including CPU, memory, battery …
[HTML][HTML] Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives
Automated development of chemical processes requires access to sophisticated algorithms
for multi-objective optimization, since single-objective optimization fails to identify the trade …
for multi-objective optimization, since single-objective optimization fails to identify the trade …
OMLT: Optimization & machine learning toolkit
The optimization and machine learning toolkit (OMLT) is an open-source software package
incorporating neural network and gradient-boosted tree surrogate models, which have been …
incorporating neural network and gradient-boosted tree surrogate models, which have been …
Computation offloading and service caching for intelligent transportation systems with digital twin
Mobile edge computing (MEC) provides a novel computing paradigm to satisfy the
increasing computation requirements of mobile applications. In MEC-enabled intelligent …
increasing computation requirements of mobile applications. In MEC-enabled intelligent …
[HTML][HTML] Maximizing information from chemical engineering data sets: Applications to machine learning
It is well-documented how artificial intelligence can have (and already is having) a big
impact on chemical engineering. But classical machine learning approaches may be weak …
impact on chemical engineering. But classical machine learning approaches may be weak …
Prospective analysis of the optimal capacity, economics and carbon footprint of energy recovery from municipal solid waste incineration
A more circular economy can have broad implications on energy recovery from municipal
solid waste (MSW) incineration. Here we present an optimization framework to assess the …
solid waste (MSW) incineration. Here we present an optimization framework to assess the …
[HTML][HTML] Formulating data-driven surrogate models for process optimization
Recent developments in data science and machine learning have inspired a new wave of
research into data-driven modeling for mathematical optimization of process applications …
research into data-driven modeling for mathematical optimization of process applications …
Comparative study of optimization method and optimal operation strategy for multi-scenario integrated energy system
Integrated energy system as a welcome multiple-energy system has significant contribution
to alleviate the worldwide energy shortage problem. In this paper, the theoretical model of …
to alleviate the worldwide energy shortage problem. In this paper, the theoretical model of …