Source code and instances for the computational experiments of the paper "Benders Adaptive-Cuts Method for Two-Stage Stochastic Programs" by Cristian Ramírez-Pico, Ivana Ljubić and Eduardo Moreno. arXiv:2203.00752
It applies different Benders methods and other optimization methods to solve three stochastic network flow problems. Each problem as its own class file and a run-file to execute an instance
Problems are:
- Stochastic Capacity Planning Problem
- Class:
cpp.py - Run file:
runCPP.py - Instances:
CPP_instances/
- Class:
- Stochastic Multicommodity Flow Problem
- Class:
smcf.py - Run file:
runSMCF.py - Instances:
SMCF_instances/
- Class:
- Facility Location with CVaR
- Class:
flcvar.py - Run file:
runFLcvar.py - Instances:
instancesFlcvar/
- Class:
It requires NumPy library and Gurobi (https://www.gurobi.com) as optimization solver.