or-tools - CP-SAT 在创建目标函数时很慢

Question

您能否向我解释一下 CP-SAT 在创建目标函数时做了什么？对于大型模型，此操作非常缓慢。功能如下：

sum(sum(self.suggested_decisions[r][d]*(
    ((int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CA_S1'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FA']*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CB_S1'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FB']*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CC_S1'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FC']*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CD_S1'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FD']*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CE_S1'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FE']*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_1'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CA_S2'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FA']*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CB_S2'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FB']*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CC_S2'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FC']*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CD_S2'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FD']*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CE_S2'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FE']*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_2'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CA_S3'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FA']*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CB_S3'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FB']*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CC_S3'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FC']*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CD_S3'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FD']*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CE_S3'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FE']*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_3'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CA_S4'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FA']*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CB_S4'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FB']*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CC_S4'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FC']*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CD_S4'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FD']*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CE_S4'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FE']*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_4'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CA_S5'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FA']*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CB_S5'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FB']*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CC_S5'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FC']*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CD_S5'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FD']*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CE_S5'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FE']*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_5'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CA_S6'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FA']*self.scenario.dataset['BandA'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CB_S6'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FB']*self.scenario.dataset['BandB'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CC_S6'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FC']*self.scenario.dataset['BandC'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CD_S6'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FD']*self.scenario.dataset['BandD'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]))+
    (int(self.scenario.dataset['CAPITAL'][r])*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_6'][r]*int(self.scenario.constants['scaling_factor']*self.scenario.constants['recovery_rate_CE_S6'])*self.scenario.decisions[d].attributes['max_capital_recoverable']-int(self.scenario.constants['scaling_factor']*self.scenario.decisions[d].attributes['FE']*self.scenario.dataset['BandE'][r]*self.scenario.dataset['SCORE_CLASS_6'][r])))
    *(1*self.scenario.constants['scaling_factor']-int(self.scenario.constants['scaling_factor']*self.scenario.dataset['SCORE'][r]))
)for r in self.all_records) for d in self.all_decisions)

其中所有 self.all_records=60.000 和 self.all_decisions=7

语言是python。

标签： or-tools

Answer 1

sum() API 创建了一个不平衡的语法树，对于大型目标进行解析非常昂贵。

我建议使用cp_model.LinearExpr.ScalProd(variable_list, coefficient_list)（见文档条目）