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整线优化第一版论文定稿工程

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增加了整线批量测试
修改了现有min-max模型路径
修改了遗传算法整体框架
估计器增加异常数据剔除
封装优化结果类
修改供料器扫描算法中重复吸嘴组的判定
This commit is contained in:
hit-lu
2024-06-26 09:44:08 +08:00
parent cbeba48da0
commit 37f4e5b02c
14 changed files with 749 additions and 669 deletions
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32
base_optimizer/optimizer_interface.py
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@ -10,33 +10,33 @@ from base_optimizer.smopt_mathmodel import *
from base_optimizer.result_analysis import *
def base_optimizer(machine_index, pcb_data, component_data, feeder_data=None, method='', hinter=False):
def base_optimizer(machine_index, pcb_data, component_data, feeder_data, params, hinter=False):
if method == 'cell-division': # 基于元胞分裂的遗传算法
if params.machine_optimizer == 'cell-division': # 基于元胞分裂的遗传算法
component_result, cycle_result, feeder_slot_result = optimizer_celldivision(pcb_data, component_data)
placement_result, head_sequence = greedy_placement_route_generation(component_data, pcb_data, component_result,
cycle_result, feeder_slot_result)
elif method == 'feeder-scan': # 基于基座扫描的供料器优先算法
elif params.machine_optimizer == 'feeder-scan': # 基于基座扫描的供料器优先算法
component_result, cycle_result, feeder_slot_result = feeder_priority_assignment(component_data, pcb_data)
placement_result, head_sequence = greedy_placement_route_generation(component_data, pcb_data, component_result,
cycle_result, feeder_slot_result)
# placement_result, head_sequence = beam_search_for_route_generation(component_data, pcb_data, component_result,
# cycle_result, feeder_slot_result)
elif method == 'hybrid-genetic': # 基于拾取组的混合遗传算法
elif params.machine_optimizer == 'hybrid-genetic': # 基于拾取组的混合遗传算法
component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_hybrid_genetic(
pcb_data, component_data, hinter=hinter)
elif method == 'aggregation': # 基于batch-level的整数规划 + 启发式算法
elif params.machine_optimizer == 'aggregation': # 基于batch-level的整数规划 + 启发式算法
component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_aggregation(
component_data, pcb_data)
elif method == 'genetic-scanning':
elif params.machine_optimizer == 'genetic-scanning':
component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_genetic_scanning(
component_data, pcb_data, hinter=hinter)
elif method == 'mip-model':
elif params.machine_optimizer == 'mip-model':
component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_mathmodel(
component_data, pcb_data, hinter=hinter)
elif method == "two-phase":
elif params.machine_optimizer == "two-phase":
component_result, feeder_slot_result, cycle_result = gurobi_optimizer(pcb_data, component_data, feeder_data,
initial=True, partition=True,
reduction=True, hinter=hinter)
@ -44,17 +44,21 @@ def base_optimizer(machine_index, pcb_data, component_data, feeder_data=None, me
placement_result, head_sequence = scan_based_placement_route_generation(component_data, pcb_data,
component_result, cycle_result)
else:
raise 'machine optimizer method ' + method + ' is not existed'
raise 'machine optimizer method ' + params.method + ' is not existed'
print('----- Placement machine ' + str(machine_index) + ' ----- ')
opt_res = OptResult(component_result, cycle_result, feeder_slot_result, placement_result, head_sequence)
# 估算贴装用时
info = placement_info_evaluation(component_data, pcb_data, component_result, cycle_result, feeder_slot_result,
placement_result, head_sequence, hinter=False)
info = placement_info_evaluation(component_data, pcb_data, opt_res, hinter=False)
if hinter:
optimization_assign_result(component_data, pcb_data, component_result, cycle_result, feeder_slot_result,
nozzle_hinter=True, component_hinter=True, feeder_hinter=True)
optimization_assign_result(component_data, pcb_data, opt_res, nozzle_hinter=True, component_hinter=True,
feeder_hinter=True)
info.print()
print('------------------------------ ')
print('------------------------------ ')
if params.save:
output_optimize_result(
f'result/{params.filename[:-4]}-{params.line_optimizer}-M0{machine_index} {params.save_suffix}',
component_data, pcb_data, opt_res)
return info