HTSim/Order.py

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