"""
Bus scheduling in cpmpy.

Problem from Taha "Introduction to Operations Research", page 58.

This is a slightly more general model than Taha's.

The model first finds the optimal value (26) and then shows all
the 145 optimal solutions.

Model created by Hakan Kjellerstrand, hakank@hakank.com
See also my cpmpy page: http://www.hakank.org/cpmpy/

"""
from cpmpy import *
from cpmpy.solvers import *
import numpy as np
from cpmpy_hakank import *

def bus_schedule(num_buses_check=0):

    # data
    time_slots = 6
    demands = [8, 10, 7, 12, 4, 4]
    max_num = sum(demands)
    x = intvar(0, max_num,shape=time_slots, name="x")
    num_buses = intvar(0, max_num,name="num_buses")

    if num_buses_check > 0:
        model = Model([num_buses == num_buses_check])
    else:
        model = Model(minimize=num_buses)

    # Constraints
    model += [num_buses >= 0, num_buses == sum(x)]

    # Meet the demands for this and the next time slot
    model += [x[i]+x[i+1] >= demands[i] for i in range(time_slots-1)]

    # The demand "around the clock"
    model += [x[time_slots-1] + x[0] == demands[time_slots-1]]

    def print_sol():
        print("num_buses: ", num_buses.value())
        print("x:", x.value())
        

    ss = CPM_ortools(model)    
    if ss.solve():
        print("num_buses: ", num_buses.value())
        print("x:", x.value())
        if num_buses_check > 0:
            num_solutions = ss.solveAll(display=print_sol)
            print("Nr solutions:", num_solutions)
    else:
        print("No solution")

    print()
    print("Num conflicts:", ss.ort_solver.NumConflicts())
    print("NumBranches:", ss.ort_solver.NumBranches())
    print("WallTime:", ss.ort_solver.WallTime())
    print()
    
    # And return the value for usage later
    return num_buses.value()
        
print("Find optimal value:")
num_buses_check = bus_schedule()
print("\nShow all solutions for", num_buses_check)
bus_schedule(num_buses_check)