Simpy:一个基于Simpy的RMFS仿真

Question

我有一个项目，我试图模拟一个RMFS仓库与simpy。我真的很感激任何人都能帮助我，因为我刚开始学习，而且我不知道如何去模仿它。我试过不同的密码，但没有一种能发挥应有的作用。这里是我的假设: 1-仓库是一个网格，每个单元格包含许多数量的1类项目(项目1、2、3、.)，.something就像附加的照片一样。它有一个唯一的地址2-订单在一个预定义的时间内到达(就像均匀分布的2分钟) 3-然后命令被分配给一个机器人(我们有10个机器人)去检索订单。这将需要3分钟，4-然后机器人交付到工作站下一个步骤(如从机器人中挑选订单，并包装)。需要2分钟。然后机器人去把订单放回去，等待下一个订单。

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Answer 1

试了一试，我模拟的过程是

基本程序：

• 订单到达，

• order得到一个机器人(如果所有的机器人都在使用的话，请排队)，

• order获取单元格(如果单元格已被另一个命令捕获)，

细胞

• pick，

• 放回单元格，

• 释放机器人

因此，相反，将单元格作为一个资源池(需要一个匹配的函数来获得所需的单元)，每个单元都有自己的容量为1的资源库。

在事后看来，我认为如果我能在抓取机器人之前先命令抓住手机，我就能获得更好的吞吐量。

"""
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)

Answer 2

这是考虑到6*9仓库的代码的更新。我还增加了一个提升装置。我很感谢你对我们如何改进和优化它的意见。以及如何将报告添加到其中。

"""
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)