Marcos Dominguez Velad (23 notebooks)#
Book Example: Economic equilibria#
Description: economic model using complementarity conditions from Chapter 19 AMPL book
Book Example: Transshipment problem#
Description: book example with general transshipment model (net1.mod)
Book Example: diet#
Description: book example autogenerated using diet.mod, diet.dat, and diet.run
Containers scheduling#
Description: Scheduling model for harbor operations. It is a problem with dependences between containers, which should be dispatch the fastest possible. We are using the MP solver interfaces to model a complex system using techniques from Constraint Programming, such as indicator constraints, and logical or and forall operators. After the model is written, a couple instances are presented and Highs/Gurobi MIP solvers are used to tackle the problem.
Diet lecture#
Description: Diet case study
Tags: ampl-only, ampl-lecture
Employee Scheduling Optimization#
Description: Employee scheduling model from the Analytical Decision Modeling course at the Arizona State University.
Google Hashcode 2022#
Description: Google Hashcode 2022 Practice Problem
Hospitals-Residents MIP#
Description: hospitals-residents problem with ties problem solved with ampl and highs
Labs scheduling#
Description: Model for laboratories scheduling. Some labs are needed to handle requests from researchers, and departments have to assign labs and locations to the requests.
Largest small polygon#
Description: lecture about models for the Largest Small Polygon Problem
Magic sequences#
Description: Solving magic sequences through reinforced formulations and constrained programming. Some comparison between models and solvers is done, and we look into the “Another solution” problem for these sequences.
Tags: constraint-programming, educational, mp, sequences, arithmetic, reinforced-formulations, highs, gecode, cbc, mip
Multicommodity transportation problem#
Description: Multicommodity transportation model with binary variables
NFL Team Rating#
Description: NFL Team Rating problem from the Analytical Decision Modeling course at the Arizona State University.
Nonlinear transportation model#
Description: book example autogenerated using nltransd.mod, nltrans.dat, and nltrans.run
Nonlinear transportation problem example#
Description: book example autogenerated using nltransd.mod, nltrans.dat, and nltrans.run
Optimization Methods in Finance: Chapter 3#
Description: Optimization Methods in Finance: Bond Dedication Problem.
P-Median problem#
Description: this notebook states the p-median problem with a simple example, and a MIP formulation in amplpy. The problem is parametrized with a class, so it is easier to sample and replicate experiments. A graphical solution is plotted.
Production model#
Description: generic model for production problem
Steel industry problem#
Description: model for steel production problem
Sudoku Generator#
Description: Generate Sudoku boards with unique solution via iterative method and mip formulation.
Supply chain network#
Description: Compute optimal routes to connect suppliers/demanding nodes in a network. Routes have an associated fixed and variable cost. There are different products to ship. The problem is formulated as a MIP with binary variables. Python data structures are used to load the data into the model.
Transportation problem#
Description: an AMPL model for the transportation problem
Tags: ampl-only, ampl-lecture
Warehouse location and transport#
Description: Model for warehouse allocation. Farms (suppliers) send feedstock to warehouses, and later on, those warehouses send it to a production plant. The problem involves modeling a storage facility location problem with a transportation component to the final plant.