65 lines
4.0 KiB
Python
65 lines
4.0 KiB
Python
# 用于提供对外接口
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from base_optimizer.smopt_scanbased import *
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from base_optimizer.smopt_celldivision import *
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from base_optimizer.smopt_hybridgenetic import *
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from base_optimizer.smopt_feederpriority import *
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from base_optimizer.smopt_aggregation import *
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from base_optimizer.smopt_twophase import *
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from base_optimizer.smopt_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, params, hinter=False):
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if params.machine_optimizer == '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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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 params.machine_optimizer == 'feeder-scan': # 基于基座扫描的供料器优先算法
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component_result, cycle_result, feeder_slot_result = feeder_priority_assignment(component_data, pcb_data)
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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 params.machine_optimizer == '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=hinter)
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elif params.machine_optimizer == '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 params.machine_optimizer == '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=hinter)
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elif params.machine_optimizer == '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=hinter)
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elif params.machine_optimizer == "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 'machine optimizer method ' + params.method + ' is not existed'
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print('----- Placement machine ' + str(machine_index) + ' ----- ')
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opt_res = OptResult(component_result, cycle_result, feeder_slot_result, placement_result, head_sequence)
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# 估算贴装用时
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info = placement_info_evaluation(component_data, pcb_data, opt_res, hinter=False)
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if hinter:
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optimization_assign_result(component_data, pcb_data, opt_res, nozzle_hinter=True, component_hinter=True,
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feeder_hinter=True)
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info.print()
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print('------------------------------ ')
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if params.save:
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output_optimize_result(
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f'result/{params.filename[:-4]}-{params.line_optimizer}-M0{machine_index} {params.save_suffix}',
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component_data, pcb_data, opt_res)
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return info
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