This project is designed for educational purposes as project of the corse of Model-Driven Decision Methods a.a 2015/16 (University Of Pisa). The goal is to implement a Linear Programming Model with PuLP and solve it with at least two different solvers, like CBC and GUROBI (Accademic License) in this case (feel free to use whatever you want/need). At last optimize one of these in order to improve performance.

I wrote a simple report (in Italian) as description of the work done. If you need it please contact me.

This is what you need before running:

• Python 3.x
• PuLP - as Python module
• Pandas - as Python module
• Numpy - as Python module
• CBC
• GUROBI

A brief description of project contents:

• module. py - implementation of PCTSPTW problem and solver call
• instance_utility. py - instances generators and other utility functions
• data/ - contains all instances
• src/ - source files

Solve one instance by using CBC with max time 600s:

$ python3 src/model.py instance.dat CBC 600

Solve a set of instance by using GUROBI with max time 10s:

$ python3 src/model.py /path/to/instances_folder/ GUROBI 10

Alessandro Romano