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增加了HSMO整线优化方法，读取数据增加了供料器部分

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hit-lu
2025-08-10 16:58:42 +08:00
parent 045f2f394d
commit 4fd5560650
17 changed files with 1765 additions and 352 deletions
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43
base_optimizer/smopt_hybridgenetic.py
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@@ -1,5 +1,5 @@
from base_optimizer.optimizer_common import *
from base_optimizer.smtopt_route import *
def dynamic_programming_cycle_path(cycle_placement, cycle_points):
head_sequence = []
@@ -231,8 +231,8 @@ def cal_individual_val(component_nozzle, component_point_pos, designated_nozzle,
def convert_individual_2_result(component_data, component_point_pos, designated_nozzle, pickup_group,
pickup_group_cycle, pair_group, feeder_lane, individual):
component_result, cycle_result, feeder_slot_result = [], [], []
placement_result, head_sequence_result = [], []
# === 记录不同元件对应的槽位 ===
feeder_part_arrange = defaultdict(list)
@@ -273,26 +273,7 @@ def convert_individual_2_result(component_data, component_point_pos, designated_
pickup_cycle_result[idx][head] -= cycle
component_point_index = defaultdict(int)
for cycle_set in range(len(cycle_result)):
for cycle in range(cycle_result[cycle_set]):
placement_result.append([-1 for _ in range(max_head_index)])
mount_point = [[0, 0] for _ in range(max_head_index)]
for head in range(max_head_index):
part_index = component_result[cycle_set][head]
if part_index == -1:
continue
part = component_data.iloc[part_index]['part']
point_info = component_point_pos[part][component_point_index[part]]
placement_result[-1][head] = point_info[2]
mount_point[head] = point_info[0:2]
component_point_index[part] += 1
head_sequence_result.append(dynamic_programming_cycle_path(placement_result[-1], mount_point))
return component_result, cycle_result, feeder_slot_result, placement_result, head_sequence_result
return component_result, cycle_result, feeder_slot_result
@timer_wrapper
@@ -510,11 +491,6 @@ def optimizer_hybrid_genetic(pcb_data, component_data, hinter=True):
pop_val.append(val) # val is related to assembly time
for _ in range(n_generations):
# idx = np.argmin(pop_val)
# if len(best_pop_val) == 0 or pop_val[idx] < best_pop_val[-1]:
# best_individual = copy.deepcopy(population[idx])
# best_pop_val.append(pop_val[idx])
# min-max convert
max_val = 1.5 * max(pop_val)
convert_pop_val = list(map(lambda v: max_val - v, pop_val))
@@ -565,6 +541,15 @@ def optimizer_hybrid_genetic(pcb_data, component_data, hinter=True):
pbar.update(1)
best_individual = population[np.argmin(pop_val)]
component_result, cycle_result, feeder_slot_result = convert_individual_2_result(component_data,
component_point_pos,
designated_nozzle, pickup_group,
pickup_group_cycle, pair_group,
feeder_lane, best_individual)
placement_result, head_sequence_result = place_cluster_greedy_route_generation(component_data, pcb_data,
component_result, cycle_result,
feeder_slot_result)
return component_result, cycle_result, feeder_slot_result, placement_result, head_sequence_result
return convert_individual_2_result(component_data, component_point_pos, designated_nozzle, pickup_group,
pickup_group_cycle, pair_group, feeder_lane, best_individual)