CPModel_ALBP.py

from docplex.cp.model import CpoModel
from docplex.cp.config import context

context.solver.agent = 'local'
context.solver.local.execfile = '/Applications/CPLEX_Studio_Community129/cpoptimizer/bin/x86-64_osx/cpoptimizer'


# """ Initialize the problem data """
# # operating time of task i
# TaskTime = [81, 109, 65, 51, 92, 77, 51, 50, 43, 45, 76]
#
# # number of workstations
# nbStations = 5
#
# # immediate precedence tasks of task i
# PrecedenceTasks = [
#     [],
#     [1],
#     [1],
#     [1],
#     [1],
#     [1, 2],
#     [1, 3, 4, 5],
#     [1, 2, 6],
#     [1, 3, 4, 5, 7],
#     [1, 2, 6, 8],
#     [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]]
#


def ALBP(TaskTime, nbStations, PrecedenceTasks):
    """ Prepare the data for modeling """
    # tasks set
    TASKS = range(len(TaskTime))
    # workstations set
    WORKSTATIONS = range(nbStations)

    """ Build the model """
    # Create CPO model
    myModel = CpoModel()

    # Assign tasks to workstation
    WhichWorkstation = myModel.integer_var_list(len(TaskTime), 0, nbStations - 1)

    # Cycle time
    CycleTime = myModel.integer_var(max(TaskTime), sum(TaskTime))

    # Add station load constraints
    for k in WORKSTATIONS:
        myModel.add(sum(TaskTime[i] * (WhichWorkstation[i] == k) for i in TASKS) <= CycleTime)

    # Add precedence constraints
    for i in TASKS:
        for j in PrecedenceTasks[i]:
            myModel.add(WhichWorkstation[j] <= WhichWorkstation[i])

    # Create model objective
    myModel.add(myModel.minimize(CycleTime))

    """ Solve model """
    solution = myModel.solve(FailLimit=100000, TimeLimit=10)


    """ Print solution """
    return solution