基于连续线性规划的多炼厂生产计划优化方法

doi:10.6040/j.issn.1671-9352.0.2023.457

Abstract

Abstract:

To enhance the profitability of integrated oil companies and address the optimization problem of multi-refinery production planning with integer variables and non-convex bilinear constraints, we established an optimization model for multi-refinery production planning using operations research methods by holistically optimizing the allocation of crude oil among multiple refineries, the load of each refinery's units, and the product slate. We proposed a solution method for mixed integer nonlinear programming (MINLP) based on successive linear programming (SLP) and introduced a branching strategy tailored to business characteristics, enabling the solution process to converge rapidly and provide high-quality solutions. Validation analysis using actual data from a petroleum enterprise demonstrated that the proposed algorithm offered advantages in both the model's objective value and solution efficiency.

Key words: multi-refinery, production planning, mixed integer nonlinear programming, successive linear programming, branching strategy

CLC Number:

O221.2

Fenglian DONG,Fengsheng ZHANG,Zhiwei WEI,Xin SUN,Yuewen LI. A petroleum multi-refinery production optimization method based on successive linear programming[J].JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2024, 59(11): 100-109, 125.

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References 25

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集合符号	含义	集合符号	含义
N	节点	E_m^I	可加工m物料的装置
N^R	炼厂型节点	E_m^O	可产出m物料的装置
N^F	非炼厂型节点	M	物料
E	装置	M_e	装置e进料
E^D	调和池	M^{(m, m′)}	可以产出物料m的进物料m′
E^G	常压装置	M_e^I	进入装置e的物料
E^H	减压装置	M^Z	总部物料
E^U	二次加工装置	Q	物性

参数符号	含义
C_{r, m}^P	r炼厂原料采购价格, r∈N^R, m∈M
C_{r, m}^S	r炼厂产品销售价格, r∈N^R, m∈M
C_{n, z}^P	n节点原料采购价格, n∈N, z∈M^Z
C_{n, z}^S	n节点产品销售价格, n∈N, M^Z
C_{n, n′, z}	n节点到n′节点运输物料z的单位运费, n∈N, n′∈N, M^Z
A_{r, e, q, m′, m}	r炼厂二次加工装置e的进料m′将物性q传递给出料m的系数, r∈N^R，e∈E^U, q∈Q, m′∈M_e, m∈M
B_{r, e, q, m′, m}	r炼厂二次加工装置e的进料m′将物性q传递给出料m的偏置, r∈N^R，e∈E^U, q∈Q, m′∈M_e, m∈M
α_{r, e, m′, m}	r炼厂装置e加工物料m′产出物料m的收率, r∈N^R, e∈E, m′∈M_e, m∈M
β_{r, m, q}、γ_{r, m, q}	炼厂r中物料m的q物性上、下限, r∈N^R, m∈M, q∈Q
β_{r, m}^P、γ_{r, m}^P	炼厂r中物料m的采购量上、下限, r∈N^R, m∈M
β_{r, m}^S、γ_{r, m}^S	炼厂r中物料m的销售量上、下限, r∈N^R, m∈M
β_{r, m}^V、γ_{r, m}^V	炼厂r中物料m的期末库存上、下限, r∈N^R, m∈M
β_{r, e}、γ_{r, e}	炼厂r装置e的加工能力上、下限, r∈N^R, e∈E
β_{n, z}^P、γ_{n, z}^P	节点n中物料z的采购量上、下限, n∈N, M^Z
β_{n, z}^S、γ_{n, z}^S	节点n中物料z的销售量上、下限, n∈N, M^Z
β_{n, z}^V、γ_{n, z}^V	节点n中物料z的期末库存上、下限, n∈N, z∈M^Z
β_{n, n′}、γ_{n, n′}	节点n到节点n′的运输量上、下限, n∈N, n′∈N

变量符号	含义
x_{r, e, m}	炼厂r装置e中物料m的进(出)量, r∈N^R, e∈E, m∈M
x_{r, m}^P	炼厂r物料m的进厂量, r∈N^R, m∈M
x_{r, m}^S	炼厂r物料m的出厂量, r∈N^R, m∈M
x_{r, m}^OPEN	炼厂r中物料m的期初库存, r∈N^R, m∈M
x_{r, m}^CLOSE	炼厂r中物料m的期末库存, r∈N^R, m∈M
x_{r, m, q}	炼厂r物料m的q物性值, r∈N^R, m∈M, q∈Q
w_{r, e}	炼厂r装置e启停(0-1变量), r∈N^R, e∈E
x_{r, e}	炼厂r装置e的加工量, r∈N^R, e∈E
y_{n, z}^P	节点n中物料z的采购量, n∈N, z∈M^Z
y_{n, z}^S	节点n中物料z的销售量, n∈N, z∈M^Z
y_{n, z}^OPEN	节点n中物料z的期初库存, n∈N, z∈M^Z
y_{n, z}^CLOSE	节点n中物料z的期末库存, n∈N, z∈M^Z
y_{n, n′, z}	节点n到节点n′运输物料z的量, n∈N, n′∈N, z∈M^Z

算例	N^R	M	Q	E	E^G	E^H	E^U
1	3	854	37	128	7	7	113
2	5	1 400	37	212	11	11	185

算例	变量个数	约束个数	整数变量个数	非线性约束个数
1	18 212	8 614	78	3 070
2	28 933	13 556	96	4 764

A petroleum multi-refinery production optimization method based on successive linear programming

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算例	Baron		人工方法+SLP		本文算法
算例	最优目标值	时间/s	最优目标值	时间/s	最优目标值	时间/s
1	—	>7 200	152 985.30	30	157 980.32	1 825
2	—	>7 200	192 352.61	55	201 632.70	3 263

算法	关停装置	原油MC的分配方案(单位：万吨)
算法	关停装置	炼厂1	炼厂2	炼厂3	合计
人工方法+SLP	炼厂1的第一套常压、第一套减压、第二套柴油加氢精制、渣油加氢，共4套装置	0	30.9	39.1	70.0
本文算法	炼厂2的第二套常压、第二套减压、第二套催化裂化、第二套气体分馏，炼厂1的渣油加氢，共5套装置	19.5	0	50.5	70.0

算法	关停装置	汽油生产方案(单位：万吨)
算法	关停装置	炼厂4	炼厂5	炼厂6	炼厂7	炼厂8	合计
人工方法+SLP	炼厂7的第一套常压、第一套减压、第一套催化裂化，共3套装置	22.1	15.8	20.4	12.5	19.2	90.0
本文算法	炼厂6的第一套常压、第一套减压、第二套催化裂化、烷基化，炼厂8的第三套催化裂化，共5套装置	22.1	15.8	14.2	20.8	17.1	90.0

算例	E^G-E^H-E^U		E^G-E^U-E^H		E^H-E^G-E^U		Strong Branching
算例	分支次数	求解时间/s	分支次数	求解时间/s	分支次数	求解时间/s	分支次数	求解时间/s
1	381	1 825	425	2 104	382	1 843	434	2 142
2	511	3 263	616	4 037	552	3 516	593	3 962

算例	只对物性变量进行信赖域控制	对全部变量进行信赖域控制
1	1 825	1 922
2	3 263	3 434

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