CP Optimizer CPLEX - Multiple optimal solutions

Question

I am currently using the Python API of the CP Optimizer of CPLEX to obtain the optimal solution of a scheduling problem. Depending on the instance, there might be multiple equivalent optimal solutions.

I would assume that during the searching process, multiple optimal solutions might be found, and thus, I would like to store them.

I have been searching the whole internet looking for ways to do that, but I haven't found any information so far. I know that this is possible to do for CPLEX (with MIP models) using a solution pool, however, for the CP Optimizer I didn't find anything. Can somebody share some information on this or at least tell me that it is not possible?

Answer 1

You can use iterators. See example at https://github.com/AlexFleischerParis/zoodocplex/blob/master/zooseveralcpo.py

from docplex.cp.model import CpoModel

mdl = CpoModel(name='buses')

nbbus40 = mdl.integer_var(0,6,name='nbBus40')
nbbus30 = mdl.integer_var(0,6,name='nbBus30')
cost= mdl.integer_var(0,1000000,name='cost')

mdl.add(cost==nbbus40*500 + nbbus30*400)
mdl.add(cost<=4000)
mdl.add(nbbus40*40 + nbbus30*30 >= 300)

siter = mdl.start_search(SearchType='DepthFirst', Workers=1, TimeLimit=100)
# Parameters needed to avoid duplicate solutions



for msol in siter:
    print(msol[nbbus40]," buses 40 seats")
    print(msol[nbbus30]," buses 30 seats")
    print("cost = ",msol[cost])
    
    print("\n")