基于条件场景的不确定性石化供应链优化方法

doi:10.16085/j.issn.1000-6613.2019-0228

摘要/Abstract

摘要：

针对产品需求及其价格存在不确定性的石化供应链计划层最优化问题，本文建立了一种基于条件场景的石化供应链最优化方法。用多个离散场景近似随机变量概率的连续分布，根据随机变量的概率分布特征，对场景发生的概率进行参数估计，进而建立了基于场景的两阶段混合整数线性规划(MILP)模型。利用基于场景的优化结果随离散网格数增加而逐渐趋近连续的随机优化结果这一规律，给出了获得最佳离散网格数的方法，实现了计算时间成本与计算精度之间的平衡。在此基础上引入条件概率方法，利用两个随机变量间的相关性，建立了以产品价格及其需求量为不确定性的石化供应链优化方法。结果表明，与传统未考虑随机变量间相关性的一般场景划分方法相比，本文基于条件场景的随机优化方法可以更快地获得最佳场景数目，进而有效降低了计算量。

关键词: 石化供应链, 条件场景方法, 参数估值, 模拟, 随机优化, 系统工程

Abstract:

A conditional scenario based approach was proposed for the optimization of tactical level petrochemical supply chain with uncertain product demands and their prices. Based on the probability distributions of the stochastic variables, estimation on the parameters for the probability of each scenario was conducted, and a series of discretized scenarios were introduced to approximate the continuous optimization problem, and a scenario based two-stage mixed integer linear programming (MILP) model was formulated. Result of this optimization tended to approach the continuous optimization when the number of scenario increased, and based on this rule, a method to find the optimal number of scenarios was proposed, so balance between the calculation accuracy and computation time was achieved. Conditional scenario method was further introduced with regard to the correlation of two stochastic variables. Results showed that, compared with traditional method with no variables correlated, the conditional scenario based stochastic optimization method could find the optimal number of scenarios more quickly, and effectively reduce the computational effort.

Key words: supply chain of petrochemical industry, conditional expectation scenarios, parameter estimation, simulation, stochastic optimization, systems engineering

中图分类号:

TQ021.8

臧佩娴,罗祎青,袁希钢. 基于条件场景的不确定性石化供应链优化方法[J]. 化工进展, 2019, 38(11): 4815-4824.

Peixian ZANG,Yiqing LUO,Xigang YUAN. Conditional scenario based approach to the optimization of petrochemical supply chain with uncertainty[J]. Chemical Industry and Engineering Progress, 2019, 38(11): 4815-4824.

图/表 11

参考文献 25

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项目	数值/×10⁷USD
利润	6.4208066
销售额	15.573179
原料购买费用	6.1126469
原料和产品的运输费用	0.8806403
炼化厂操作费用	1.3364521
库存费用	0.0209382
额外购买的进口产品费用	0.5196594
二氧化碳排放税	0.0582422
生产过剩的惩罚费用	0.0529190
生产未满足订单的惩罚费用	0.1708746

项目	数值/×10⁷USD
利润	6.4208066
销售额	15.573179
原料购买费用	6.1126469
原料和产品的运输费用	0.8806403
炼化厂操作费用	1.3364521
库存费用	0.0209382
额外购买的进口产品费用	0.5196594
二氧化碳排放税	0.0582422
生产过剩的惩罚费用	0.0529190
生产未满足订单的惩罚费用	0.1708746

场景	产品价格	概率/%
1	μ_p-2σ_p	2.28
2	μ_p-1σ_p	13.59
3	μ_p	68.26
4	μ_p+1σ_p	13.59
5	μ_p+2σ_p	2.28

场景	产品价格	概率/%
1	μ_p-2σ_p	2.28
2	μ_p-1σ_p	13.59
3	μ_p	68.26
4	μ_p+1σ_p	13.59
5	μ_p+2σ_p	2.28

N	一般场景划分方法/s	条件场景方法/s
1	0.709	0.709
5	25.319	2.123
11	148.280	4.720
15	1455.413	7.035
23	11359.641	15.909
29	33076.649	23.990