针对炼油厂系统性运营优化问题的混合分布递归及分支定界算法

doi:10.15960/j.cnki.issn.1007-6093.2025.04.012

Abstract

Abstract:

The optimization of refinery operations is a critical issue within the crude oil supply chain, garnering extensive research and application interest across both academic and industrial sectors. Typically, refinery optimization problems are modeled as Mixed Integer Non-Linear Programming (MINLP) problems. The complexity of these problems arises from the vast diversity of crude oil types and their derivative products, coupled with intricate processing procedures. Moreover, specific processing steps involve changes in material properties and rules, introducing non-convex, nonlinear, and integer constraints, which increase the solution-finding difficulty. Currently, academic research primarily focuses on modeling and solving small-scale issues or subsystems of operational processes. Commercial solvers like BARON and DICOPT in GAMS are commonly employed for such tasks. This paper introduces a Hybrid Distribution Recursion and Branch and Bound algorithm (Hybrid-DRBB) for solving MINLP in refinery optimization. This method relaxes and solves nonlinear and integer constraints separately, thereby obtaining near-optimal solutions for the original problem. Through numerical experiments utilizing real-world, large-scale data scenarios, we demonstrate the efficiency of our method in comparison to traditional commercial solvers, highlighting its reduced computational cost and improved solving approach.

Key words: refinery optimization, MINLP, distribution recursion algorithm, branch and bound algorithm

CLC Number:

O221.2

Xin SUN, Dongdong GE, Desheng FU, Zhiwei WEI, Fenglian DONG, Shichang PAN. A hybrid distribution recursion and branch and bound algorithm for Petroluem refinery optimization problem[J]. Operations Research Transactions, 2025, 29(4): 141-158.

Figures/Tables 7

References 29

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集合	注释
$ m $	物料, $ m=\{mi, mb, mq, mrc, mr, ms, mv, my\} $
$ mi $	原油切割馏分, $ mi=\{ma, mrc, mv\} $
$ e $	装置, $ e=\{bu, c, v, u, b, sa\} $
$ p $	二次装置加工方案
$ q $	物性
$ tj $	二次装置中条件操作变量
$ d $	delta-base结构
$ cap $	加工能力, $ cap=\{capc, capv, capu\} $
$ ul $	公用工程, $ ul=\{ulp, uls\} $
$ I_{e, m} $	物料$ m $以进料的方式进入装置$ e $的集合, $ \{e, m\} \in I_{e, m} $
$ O_{e, m} $	物料$ m $以出料的方式进入装置$ e $的集合, $ \{e, m\} \in O_{e, m} $

连续变量	注释
$ WM_{e, m} $	装置$ e $中物料$ m $的量
$ WUL_{e, ulp} $	装置$ e $中公用工程$ ulp $的量
$ XB_{b, mb, m} $	调和池$ b $中调和物料$ mb $使用的物料$ m $的用量
$ WUP_{e, p} $	二次装置$ e $中使用方案$ p $的加工量
$ WPM_{e, p, m} $	二次装置$ e $中方案$ p $使用的物料$ m $加工量
$ Con_{e, tj, p} $	二次装置$ e $中方案$ p $的操作条件变量$ tj $
$ MatQua_{m, q} $	物料$ m $的物性$ q $的原形式
$ IndexMatQua_{m, q} $	物性$ m $的物性$ q $的指数形式
$ MatQuaP_{u, p, mq, q} $	二次装置$ u $中方案$ p $传递的某子物料$ mq $的物性$ q $原形式
$ IndexMatQuaP_{u, p, mq, q} $	二次装置$ u $中方案$ p $传递的某子物料$ mq $的物性$ q $指数形式

整数变量	注释
$ CapBi_{e} $	装置$ e $的启停, $ CapBi_{e}\in \{0, 1\} $
$ WemBi_{m} $	是否购买或销售物料$ m $, $ WemBi_{m}\in \{0, 1\} $
$ WemBatch_{m} $	物料$ m $批次量的倍数, $ WemBatch_{m}\in \{0, 1, 2, \cdots\} $
$ BldWgtBi_{b, mb, m} $	调和池$ b $中物料$ m $是否参与调和了$ mb $, $ BldWgtBi_{b, mb, m}\in \{0, 1\} $
$ BldWgtBatch_{b, mb, m} $	调和池中调和$ mb $使用物料$ m $的批次数目, $ BldWgtBatch_{b, mb, m}\in \{0, 1, 2, \cdots\} $
$ UntBasBi_{u, p} $	二次装置$ u $中是否采用方案$ p $生产, $ UntBasBi_{u, p}\in \{0, 1\} $

常数参数	注释
$ CCUT $	原油切割收率
$ WCAP $	装置加工能力
$ UDB $	原料性质影响的delta-base定义
$ UDR\_P $	二次装置中对原料性质影响的delta-base结构的幂次项收率
$ UTR $	温度压强影响下的二次装置收率
$ UTB\_\theta $	常温
$ UPR $	二次装置某方案收率
$ UPC $	常压公用工程单耗
$ UPU $	二次装置公用工程单耗
$ Price $	物料销售单价
$ Cost $	物料成本单价
$ UCost $	公用工程成本单价
$ Batch $	单位批次量
$ WemBatchBND $	采购和销售时批次量数目上下限
$ WemBND $	采购和销售时物料量上下限
$ BldWgtBiBND $	调和过程中物料使用上下限
$ BldWgtBatchBND $	调和过程中物料批次量使用上下限
$ BlendNum $	调和过程中需要的物料数目
$ M1, M2 $	生产中物料缺损量和冗余量
$ UL1, UL2 $	生产中公用工程缺损量和冗余量
$ Penalty $	关于缺损和冗余的惩罚项

算例规模	算例名称
算例规模	算例1	算例2	算例3	算例4
装置数量	67	87	115	71
物性数量	22	36	69	54
原油数量	19	12	19	18
产品数量	39	45	98	41
连续变量数目	2 068	3 215	4 640	1 885
整数变量数目	7	12	8	16
约束数目	2 218	3 583	5 269	2 045

		算例名称
		算例1	算例2	算例3	算例4
Hybrid-DRBB	求解时间	24	42	124	297
	是否有可行解	是(已收敛)	是(已收敛)	是(已收敛)	是(已收敛)
	目标函数值	40 224	1 408 388	145 016	35 648
	GAP/%	0.01	—	—	0.9
BARON	求解时间	33	1 800	1 800	1 800
	是否有可行解	是(且最优)	否	否	是
	目标函数值	40 220	—	—	41 124
	GAP/%	0	—	—	16.4
ANTIGONE	求解时间	27	1 800	1 800	1 608
	是否有可行解	是(且最优)	否	否	是(且最优)
	目标函数值	40 220	—	—	35 320
	GAP/%	0	—	—	0

A hybrid distribution recursion and branch and bound algorithm for Petroluem refinery optimization problem

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