Intro a Pesquisa Operacional - LP
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Updated
Aug 29, 2023 - HTML
Intro a Pesquisa Operacional - LP
A co-optimization model between Energy and Ancillary Service (AS) products. We pull Energy and AS prices using the Gridstatus API using Pyomo for model setup and GLPK for solver.
Python implementation of classical optimization problems
A capacitated static lot-sizing problem incorporating individual chance constraints for service levels has been addressed. The demand is uncertain and follows a uniform distribution.
This jupyter notebook uses the pyomo optimization library and ipopt solver to fit water advancement data based on the Y = X ^ r equation. This equation is used to model the advancement of water in border irrigation. X represents advancement time (min) and Y represents advancement length (m) '''
A few files from the exercises and course project in TET4185 (Power markets)
Python code that generate shift-timetable for 3 set of rules
Collection of example Jupyter Notebooks and R Markdown files for predictive analytics
Mobile Munchies is deciding how much of each type of juice to prepare for the week. Given the ingredients and cost, a python model using Pyomo and GLPK determined the optimal amount of each type of lemonade to produce so the profits maximized subject to the constraints.
Pavement maintenance management using dynamic programming
Docker container to use Pyomo with GLPK and COIN-OR
Multi-objective optimization to maximize business outcomes with python and pyomo
(Python, Pyomo) development and evaluation of a comprehensive energy production model using continuous and discrete variables. Optimization problem with a focus on minimizing costs and adhering to environmental, demand, availability constraints
Laboratory sessions for the class "Optimization & Analytics". Grade 9.7/10 (Honours)
Modelos matemáticos e heurísticas de pesquisa operacional
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