97 lines
5.3 KiB
Python
97 lines
5.3 KiB
Python
# 用于提供对外接口
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from base_optimizer.optimizer_scanbased import *
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from base_optimizer.optimizer_celldivision import *
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from base_optimizer.optimizer_hybridgenetic import *
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from base_optimizer.optimizer_feederpriority import *
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from base_optimizer.optimizer_aggregation import *
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from base_optimizer.optimizer_twophase import *
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from base_optimizer.optimizer_mathmodel import *
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from base_optimizer.result_analysis import *
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def base_optimizer(machine_index, pcb_data, component_data, feeder_data=None, method='', hinter=False):
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if method == 'cell_division': # 基于元胞分裂的遗传算法
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component_result, cycle_result, feeder_slot_result = optimizer_celldivision(pcb_data, component_data,
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hinter=False)
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placement_result, head_sequence = greedy_placement_route_generation(component_data, pcb_data, component_result,
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cycle_result, feeder_slot_result)
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elif method == 'feeder_scan': # 基于基座扫描的供料器优先算法
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# 第1步：分配供料器位置
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nozzle_pattern = feeder_allocate(component_data, pcb_data, feeder_data, figure=False)
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# 第2步：扫描供料器基座，确定元件拾取的先后顺序
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component_result, cycle_result, feeder_slot_result = feeder_base_scan(component_data, pcb_data, feeder_data,
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nozzle_pattern)
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# 第3步：贴装路径规划
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placement_result, head_sequence = greedy_placement_route_generation(component_data, pcb_data, component_result,
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cycle_result, feeder_slot_result)
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# placement_result, head_sequence = beam_search_for_route_generation(component_data, pcb_data, component_result,
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# cycle_result, feeder_slot_result)
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elif method == 'hybrid_genetic': # 基于拾取组的混合遗传算法
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component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_hybrid_genetic(
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pcb_data, component_data, hinter=False)
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elif method == 'aggregation': # 基于batch-level的整数规划 + 启发式算法
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component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_aggregation(
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component_data, pcb_data)
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elif method == 'genetic_scanning':
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component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_genetic_scanning(
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component_data, pcb_data, hinter=False)
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elif method == 'mip_model':
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component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_mathmodel(
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component_data, pcb_data, hinter=True)
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elif method == "two_phase":
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component_result, feeder_slot_result, cycle_result = gurobi_optimizer(pcb_data, component_data, feeder_data,
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initial=True, partition=True,
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reduction=True, hinter=hinter)
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placement_result, head_sequence = scan_based_placement_route_generation(component_data, pcb_data,
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component_result, cycle_result)
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else:
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raise 'method is not existed'
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info = OptInfo()
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assigned_nozzle = ['' if idx == -1 else component_data.loc[idx]['nz'] for idx in component_result[0]]
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info.cycle_counter = sum(cycle_result)
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for cycle in range(len(cycle_result)):
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pick_slot = set()
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for head in range(max_head_index):
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idx = component_result[cycle][head]
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if idx == -1:
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continue
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nozzle = component_data.loc[idx]['nz']
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if nozzle != assigned_nozzle[head]:
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if assigned_nozzle[head] != '':
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info.nozzle_change_counter += 1
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assigned_nozzle[head] = nozzle
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pick_slot.add(feeder_slot_result[cycle][head] - head * interval_ratio)
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info.pickup_counter += len(pick_slot) * cycle_result[cycle]
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pick_slot = list(pick_slot)
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pick_slot.sort()
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for idx in range(len(pick_slot) - 1):
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info.pickup_movement += abs(pick_slot[idx + 1] - pick_slot[idx])
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if hinter:
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optimization_assign_result(component_data, pcb_data, component_result, cycle_result, feeder_slot_result,
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nozzle_hinter=True, component_hinter=True, feeder_hinter=True)
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print('----- Placement machine ' + str(machine_index) + ' ----- ')
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print('-Cycle counter: {}'.format(info.cycle_counter))
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print('-Nozzle change counter: {}'.format(info.nozzle_change_counter))
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print('-Pick operation counter: {}'.format(info.pickup_counter))
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print('-Pick movement: {}'.format(info.pickup_movement))
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print('------------------------------ ')
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# 估算贴装用时
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info.placement_time = placement_time_estimate(component_data, pcb_data, component_result, cycle_result,
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feeder_slot_result, placement_result, head_sequence, hinter=False)
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return info
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