HTSim/Order.py

34 lines
1.3 KiB
Python

import agentpy as ap
import random
import numpy as np
from numpy import random
import pandas as pd
class Order(ap.Agent):
xv_time_created: int # 订单创建时间
xv_time_circle: int # 随机生成的交货周期
xv_dlv_t: int # 客户希望的交货时间
ev_actual_dlv_t: int # 实际交付时间
ev_is_delivered: bool # 订单是否已交付
ev_is_accepted: bool # 订单是否被接受
ev_int_delay_time: int # 订单延迟交付时间
xv_ary_dlv_product: np.ndarray
ev_ary_dlv_product: np.ndarray
def setup(self, time_created):
self.xv_time_created = time_created # 订单创建时间
# read the demand of 23 productions
self.xv_ary_dlv_product = np.asarray(tuple([tuple(x) for x in pd.read_excel("demand23.xlsx").values])) # 接神经网络结果
self.ev_ary_dlv_product = np.asarray(tuple(pd.read_excel("demand23.xlsx").iloc[:, 1])) # 23x1 把产品的顺序按照xv_ary_product_id重新排列!!!
self.xv_time_circle = np.random.randint(7, 11, 1)
self.xv_dlv_t = self.xv_time_created + self.xv_time_circle # 随机生成期望交付时间
self.ev_actual_dlv_t = self.xv_dlv_t
self.ev_int_delay_time = 0
# Set the initial status of order to be undelivered, accepted
self.ev_is_delivered = False
self.ev_is_accepted = False