104 lines
4.2 KiB
Python
104 lines
4.2 KiB
Python
import runtime
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import model
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import csv
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from typing import List, Dict
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from datetime import datetime
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import time
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import math
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import dataset_importer
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def orders_processor(orders: Dict[str, model.Order]) -> List[runtime.RuntimeProduct]:
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orders_list = list(orders.values())
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sorted_orders_list = sorted(orders_list, key=lambda order: order.latest_end_time)
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products_lines = runtime.RuntimeProductLines()
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for sorted_order in sorted_orders_list:
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for item in sorted_order.products:
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runtime_product = runtime.RuntimeProduct(item["product"], item["amount"])
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runtime_product.set_ddl_start(sorted_order.latest_end_time, sorted_order.earliest_start_time)
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products_lines.add_runtime_product(runtime_product)
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runtime_product = products_lines.pop_runtime_product()
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produce_tree = []
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produce_list = []
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while runtime_product is not None:
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search_semi_products(0, produce_tree, produce_list, runtime_product)
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runtime_product = products_lines.pop_runtime_product()
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return produce_list
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def search_semi_products(floor, produce_tree, produce_list, runtime_product):
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runtime_semi_products = []
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produce_tree.append({"runtime_product": runtime_product, "runtime_semi_products": runtime_semi_products})
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# print("F", runtime_product.product.product_id, runtime_product.ddl)
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if len(runtime_product.product.semi_products) > 0:
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for item in runtime_product.product.semi_products:
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runtime_semi_product = runtime.RuntimeProduct(item["semi_product"], item["amount"])
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runtime_semi_product.set_ddl_start(runtime_product.ddl, runtime_product.start)
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# print("C", runtime_semi_product.product.product_id, runtime_semi_product.ddl)
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search_semi_products(floor+1, runtime_semi_products, produce_list, runtime_semi_product)
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print("L", floor, runtime_product.product.product_id, runtime_product.ddl)
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produce_list.append(runtime_product)
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def products_processor(runtime_products: List[runtime.RuntimeProduct]):
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runtime_products_processes_list: List[Dict[str, any]] = []
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for runtime_product in runtime_products:
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processes_list: List[runtime.RuntimeProcess] = []
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production_times: int = 0
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for process in runtime_product.product.processes:
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# 执行工序的次数
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process_number = math.ceil(float(runtime_product.amount) / float(process.max_quantity))
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for i in range(process_number):
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runtime_process: runtime.RuntimeProcess = \
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runtime.RuntimeProcess(runtime_product, process)
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production_times += runtime_process.process.pdt_time
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processes_list.append(runtime_process)
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runtime_product.set_delay(production_times)
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runtime_products_processes_list.append({"runtimeProduct": runtime_product, "runtimeProcess": processes_list})
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runtime_products_processes_list = \
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sorted(runtime_products_processes_list,
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key=lambda dict_item:
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(dict_item["runtimeProduct"].ddl, dict_item["runtimeProduct"].delay))
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# 输出检查
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for item in runtime_products_processes_list:
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for runtime_process in item["runtimeProcess"]:
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runtime_product: runtime.RuntimeProduct = item["runtimeProduct"]
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print(runtime_product.product.product_id, runtime_product.delay, runtime_process.process.pcs_id)
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return runtime_products_processes_list
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# def resource_processor(resources: List[model.Resource], runtime_products_processes_list: List[Dict[str, any]]):
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# resource_pool = runtime.RuntimeResourcePool(resources)
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#
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# for item in runtime_products_processes_list:
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# ifalloc = True
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# for runtime_process in item["runtimeProcess"]:
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# runtime_process: runtime.RuntimeProcess = runtime_process
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# for resource_item in runtime_process.process.res_needs:
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# resource_item['']
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# runtime_resource_need = runtime.RuntimeResourceNeed(runtime_process.process)
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# if resource_pool.alloc_resource():
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if __name__ == "__main__":
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m_orders, m_products, m_processes, m_resources = dataset_importer.import_dataset()
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produce_list = orders_processor(m_orders)
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products_processor(produce_list) |