Sales Optimization problem with linear programming in Julia / Jupyterlab -- 2
Budget: $30 – $250 USD
The target consists of a notebook (Jupyter, JupyterLab, or Pluto) or a Julia file ( .jl ) with the algorithms and description of the ideas implemented and the results obtained.
Code
The design of the algorithms must satisfy the following criteria:
Decomposition into short and specific functions (~ 15 lines max). All logic is contained in functions.
Reproducibility of the notebook in a run from scratch. All variables used in functions are declared locally.
Documentation of the most relevant ideas in docstrings and/or markdown. Clear and precise explanations where they are needed (do not comment on all lines of code).
Legibility of functions and structure (conventions, indentation, etc). The names of functions and variables have a real and concise meaning.
Extra: It is recommended to organize the functions in an external .jl file and import them into the notebook using include() .
Code
The design of the algorithms must satisfy the following criteria:
Decomposition into short and specific functions (~ 15 lines max). All logic is contained in functions.
Reproducibility of the notebook in a run from scratch. All variables used in functions are declared locally.
Documentation of the most relevant ideas in docstrings and/or markdown. Clear and precise explanations where they are needed (do not comment on all lines of code).
Legibility of functions and structure (conventions, indentation, etc). The names of functions and variables have a real and concise meaning.
Extra: It is recommended to organize the functions in an external .jl file and import them into the notebook using include() .