Simpy: An RMFS simulation with Simpy

Question

i have a project and i am trying to simulate a RMFS warehouse with simpy. i would really appreciate it anyone can help me as i'm new to simpy and stuck and i dont know how to model it. i tried different codes but none of them work as they should. here is my assumptions: 1- the Warehouse is a grid and each cell contain many quantity of 1 type of item(item 1,2,3,...).something like the attached photo. it have a unique address 2- orders come in a predefined time (like with uniform distribution of 2 minutes) 3- the orders then is assigned to a robot (we have 10 robots) to go and retrieve the order. it will take 3 minutes 4- then the robot deliver the order to a workstation for next step (like pick the order from robot and package it). it will take 2 minutes. 5- then the robot go and put the order back and wait for next order.

Answer 1

this is the update for the code considering a 6*9 Warehouse. i also added a lifting mechanism to it. i appreciate your comments on how we can improve and optimize it. and how to add reporting to it.

"""
modes a robot warehouse where robots get pulls a cell
and brings it to a picker who picks stuff from the cell,
then returns the cell back to the warehouse

basic process:
order arrives
order gets a robot (wait in a queue if all robots are in use)
order gets cell (wait if cell has been seized by another order)
pick from cell
put cell back
release robot

programmer: Michael R. Gibbs
"""

import simpy
import random
random.seed(0)


NUM_ROBOTS = 10
NUM_PICKERS = 1
NUM_GANTRY = 2
EXT_CELLS = [1,2,3,4,5,6,7,12,13,18,19,24,25,30,31,36,37,42,43,48,49,50,51,52,53,54]
INT_CELLS = [8,9,10,11,14,15,16,17,20,21,22,23,26,27,28,29,32,33,34,35,38,39,40,41,44,45,46,47]


class Order():
    """
    Order to be fulfilled

    has unique id for tracking
    and the cell id to pull
    """

    # class var used to gen unique ids
    next_id = 1

    def __init__(self, cell):
        """
        initalizes a order with a unique id and a cell to pull
        """

        # set unique id
        self.id = Order.next_id
        Order.next_id += 1

        # set cell to pull
        self.cell = cell


class Cell():
    """
    Cell that robots retrieve so pickers can pick

    A cell can only be seized by one robot at a time
    so each cell has its own request queue implemented
    with a simple resource.
    """

    def __init__(self, env, id):
        """
        Initializes a cell with a id, and a request/resource queue
        """

        self.id = id
        self.env = env

        # used to queue requests for the cell
        self.resQueue = simpy.Resource(env, capacity=1)

        # request that currently holds the cell's resource
        self.request = None

    def seize(self):
        """
        gets in queue and waits to seize cell
        """

        request = self.resQueue.request()  # Generate a request event
        yield request

        # save the request that has the cell so can release latter
        self.request = request

        return self

    def release(self):
        """
        releases the cell so other robots can seize it
        """

        yield self.resQueue.release(self.request)
        self.request = None


def gen_orders(env, cellMap, robots):
    """
    Generates orders at a random distribution
    and kicks off the fill order process for the order
    """

    while True:
        # time between arrivals
        yield env.timeout(random.expovariate(1.0/1.5))

        # create order and assign cell
        cell = random.randint(1, len(cellMap))
        order = Order(cell)
        print('{:.2f} Order {}  received for item in cell #{}'.format(env.now, order.id,order.cell))

        # start process to fulfill the order
        # do not use yield here, just drop and go to next order
        if cell in EXT_CELLS:
            env.process(fill_order(order, cellMap, robots, pickers))
        else:
            env.process(fill_order_internal(order, cellMap, robots, pickers,gantry))




def fill_order(order, cellMap, robots, pickers):
    """
    the order filling process

    this process gets created for each order
    """
    #indicate cell status
    print(format(env.now,'.2f'), f'order {order.id} cell {order.cell} is an external cell')

    # get a robot
    print('{:.2f} order {} waits for robot'.format(env.now,order.id))
    with robots.request() as req:
        yield req
        print('{:.2f} order {} assigned to robot# {}'.format(env.now, order.id, robots.count))

        # get the cell
        print(format(env.now, '.2f'), f'order {order.id} waits for cell {order.cell}')
        cell = cellMap[order.cell]
        yield env.process(cell.seize())
        print(format(env.now, '.2f'), f'order {order.id} has seized cell {order.cell}')

        # pull the cell
        yield env.timeout(3)
        print(format(env.now,'.2f'), f'order {order.id} has pulled cell {order.cell} by robot#{robots.count}')

        # pick
        with pickers.request() as picker_req:
            yield picker_req
            yield env.timeout(random.triangular(0.5,1.2,1.8))
            print(format(env.now,'.2f'), f'order {order.id} has picked')

        # return cell
        yield env.timeout(3)
        env.process(cell.release())
        print(format(env.now,'.2f'), f'order {order.id} has return cell {order.cell} by robot# {robots.count}')

    # release robot
    print('{:.2f} order {} has released a robot'.format(env.now,order.id))


def fill_order_internal(order, cellMap, robots, pickers,gantry):
    """
    the order filling process for internal cells

    this process gets created for each order
    """
    #indicate cell status
    print(format(env.now,'.2f'), f'order {order.id} cell {order.cell} is an internal cell')
    # get a robot
    print('{:.2f} order {} waits for robot and gantry'.format(env.now,order.id))
    with robots.request() as req:
        yield req
        print('{:.2f} order {} assigned to robot# {}'.format(env.now, order.id, robots.count))


        # get the cell
        print(format(env.now, '.2f'), f'order {order.id} waits for cell {order.cell}')
        cell = cellMap[order.cell]
        yield env.process(cell.seize())
        print(format(env.now, '.2f'), f'order {order.id} has seized cell {order.cell}')

        # get the gantry
        with gantry.request() as req_gantry:
            yield req_gantry
            print('{:.2f} order {} assigned to gantry# {}'.format(env.now, order.id, gantry.count))

        #lift obstacle cells
            yield env.timeout(2)
            print(format(env.now, '.2f'), f'order {order.id} has lifted obstacles of cell {order.cell} by gantry{gantry.count}')

        # pull the cell
        yield env.timeout(3)
        print(format(env.now,'.2f'), f'order {order.id} has pulled cell {order.cell} by robot#{robots.count}')

        # pick
        with pickers.request() as picker_req:
            yield picker_req
            yield env.timeout(random.triangular(0.5,1.2,1.8))
            print(format(env.now, '.2f'), f'order {order.id} has picked')

        # get the gantry
        with gantry.request() as req_gantry:
            yield req_gantry
            print('at {:.2f} order {} assigned to gantry# {}'.format(env.now, order.id, gantry.count))

        # lift obstacle cells for return
            yield env.timeout(2)
            print(format(env.now, '.2f'), f'order {order.id} has lifted obstacles of cell {order.cell} by gantry{gantry.count}')

        # return cell
        yield env.timeout(3)
        env.process(cell.release())
        print(format(env.now,'.2f'), f'order {order.id} has return cell {order.cell} by robot# {robots.count}')

    # release robot
    print('at {:.2f} order {} has released a robot'.format(env.now,order.id))

# start building the sim
env = simpy.Environment()

# 54 cells for a 6*9 Warehouse
cellMap = {id: Cell(env, id) for id in range(1, 55)}
#print(cellMap)
robots = simpy.Resource(env, capacity= NUM_ROBOTS)
pickers = simpy.Resource(env, capacity= NUM_PICKERS)
gantry = simpy.Resource(env, capacity= NUM_GANTRY)

# start generating orders, which also kicks off the processing for each order

env.process(gen_orders(env, cellMap, robots))

env.run(100)

Answer 2

gave it a shot, the process I modeled is

basic process:

• order arrives,

• order gets a robot (wait in a queue if all robots are in use),

• order gets cell (wait if cell has been seized by another order),

• pick from cell,

• put cell back,

• release robot

so rather then have the cells be a pool of resources (that would need a matching function to get the desired cell), each cell has its own resource pool of capacity of 1. I use this to queue requests for the cell and all the cells are in a dict for easy access

in hind sight, I think I could get better throughput if I had the order seize the cell before seizing the robot.

"""
modes a robot warehouse where robots get pulls a cell
and brings it to a picker who picks stuff from the cell,
then returns the cell back to the warehouse

basic process:
order arrives
order gets a robot (wait in a queue if all robots are in use)
order gets cell (wait if cell has been seized by another order)
pick from cell
put cell back
release robot

programmer: Michael R. Gibbs
"""

import simpy
import random

class Order():
    """
    Order to be fulfilled

    has unique id for tracking
    and the cell id to pull
    """

    # class var used to gen unique ids
    next_id = 1

    def __init__(self, cell):
        """
        initalizes a order with a unique id and a cell to pull
        """

        # set unique id
        self.id = Order.next_id
        Order.next_id += 1

        # set cell to pull
        self.cell = cell

class Cell():
    """
    Cell that robots retrieve so pickers can pick
    
    A cell can only be seized by one robot at a time
    so each cell has its own request queue implemented 
    with a simple resouce.  Could have put all the cells in 
    one matching store, but I think this is more effecient
    as the matching can be slow with big queues
    """
    
    def __init__(self, env, id):
        """
        Initializes a cell with a id, and a request/resouce queue
        """

        self.id = id
        self.env = env

        # used to queue requests for the cell
        self.resQueue = simpy.Resource(env, capacity=1)

        # request that currently holds the cell's resource
        self.request = None

    def seize(self):
        """
        gets in queue and waits to seize cell
        """

        request = self.resQueue.request()  # Generate a request event
        yield request

        # save the request that has the cell so can release latter
        self.request = request

        return self

    def release(self):
        """
        releases the cell so other robots can seize it
        """

        yield self.resQueue.release(self.request)
        self.request = None

def gen_orders(env, cellMap, robots):
    """
    Generates orders at a random distrubution
    and kicks off the fill order process for the order
    """

    while True:
        # time between arrivals
        yield env.timeout(random.uniform(0,2))

        # create order and assign cell
        cell = random.randint(1,len(cellMap))
        order = Order(cell)
        print(env.now, f'Order {order.id} has been created')

        # start process to fulfill the order
        # do not use yield here, just drop and go to next order
        env.process(fill_order(order,cellMap, robots))

def fill_order(order, cellMap, robots):
    """
    the order filling process

    this process gets created for each order
    """

    # get a robot
    print(env.now, f'order {order.id} waits for robot')
    with robots.request() as req:
        yield req
        print(env.now, f'order {order.id} has a robot')

        # get the cell
        print(env.now, f'order {order.id} waits for cell {order.cell}')
        cell = cellMap[order.cell]
        yield env.process(cell.seize())
        print(env.now, f'order {order.id} has seized cell {order.cell}')
       
       # pull the cell
        yield env.timeout(3)
        print(env.now, f'order {order.id} has pulled cell {order.cell}')

        # pick
        yield env.timeout(2)
        print(env.now, f'order {order.id} has picked')

        # return cell
        yield env.timeout(3)
        env.process(cell.release())
        print(env.now, f'order {order.id} has return cell {order.cell}')

    # release robot
    print(env.now, f'order {order.id} has released a robot')


# start building the sim
env = simpy.Environment()

# made only 10 cells so orders are more likely to compete for a cell
cellMap = {id:Cell(env,id) for id in range(1,10)}

robots = simpy.Resource(env,capacity=10)

# start generating orders, which also kicks off the processing for each order
env.process(gen_orders(env, cellMap, robots))

env.run(100)