Package: dwsimopt
dwsimopt: DWSIM simulation optimization with Python!The DWSIM Optimization (dwsimopt) is a Python library that automates DWSIM simulations for process optimization.
The simulation dlls are embedded in the programming environment so that they can be accessed and modified by the optimization algorithms.Mathematical backgroundAlthough very efficient to describe in detail complex systems that would otherwise have to be simplified or approximated, black-box process simulators lack the symbolic formulation of the process model equations and the analytical derivatives that are useful for optimization, for example. The use of simulation may also introduce noise to the calculations due to convergence and approximations of numerical methods, which can jeopardize the calculation of accurate approximate derivatives and, therefore, the use of gradient-based optimization methods directly[1]. Also, the lack of analytical formulations of the optimization problem prevents the derivation of rigorous upper and lower bounds of the functions that are used for deterministic global optimization[2]. In that sense, the optimization models that require simulations to calculate the objective function and/or constraints are often referred to as simulation optimization problem[3]. A simplified version of this class of problems can be described as finding anthat solves globally the following constrained problemin which the objective functionand constraints, beingqthe number of constraints, are somewhat expensive to calculate, slightly noisy, and black-box functions,i.e.there is no available mathematical expression forforg, but for a giventhe values off(x) andf(x) are calculated in a computer code simulation with some noise.RequirementsPython <= 3.9 (python 3.8 recommended -- using python 3.9 requires installing dwsimopt fromsetup.py)DWSIM v7+ (open-source chemical process simulation.Download here)pythonnet == 2.5.2 (on Python 3.9 you'll need todownload the pythonnet2.5.2 wheelandpip install path\to\pythonnet_wheel)pywin32numpyscipyscikit-optIt is recommendable to start from a fresh environment and let thedwsimoptinstall the dependencies, seeInstallationsection. DWSIM must be downloaded and installed manually.InstallationInstall the latest version of this repository to your machinepip install dwsimoptorgit clone https://github.com/lf-santos/dwsimopt.git
cd dwsimopt
python setup.py installMake sure you have all the required packages and software. Navigate through the jupyter notebook examples. Use theOptimiSimclass to embed yourDMSWIMsimulation into Python. Add degrees of freedom, objective function and constraints from your simulation optimization problem with thepy2dwimpython-dwsim data exchange interface. Solve the problem with a suitable optimization solver (surrogate-based optimization or global optimization meta-heuristics recommended) that you can find methods in theOptimiSimclass (e.g.GA,PSO,DE)Citing usIf you use dwsimopt, please cite the following paper:L. F. Santos, C. B. B. Costa, J. A. Caballero, M. A. S. S. Ravagnani, Framework for embedding black-box simulation into mathematical programming via kriging surrogate model applied to natural gas liquefaction process optimization, Applied Energy, 310, 118537 (2022).@article{Santos2022,
title = {Framework for embedding black-box simulation into mathematical programming via kriging surrogate model applied to natural gas liquefaction process optimization},
author = {Lucas F. Santos and Caliane B.B. Costa and José A. Caballero and Mauro A.S.S. Ravagnani},
journal = {Applied Energy},
volume = {310},
pages = {118537},
year = {2022},
issn = {0306-2619},
doi = {https://doi.org/10.1016/j.apenergy.2022.118537},