mixed-integer-linear#
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.
Multicommodity transportation problem#
Description: Multicommodity transportation model with binary variables
Retrieve Solution pool with AMPL and Gurobi#
Description: This notebook describes how to retrieve multiple solutions from the solver’s solution pool. Optimization problems usually have several optimal solutions, one is returned by the solver but the others are discarded. These alternative solutions can also be retrieved by AMPL.
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.
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.