Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming

Based on actual lubricating oil production data and the base oil performance indexes of an enterprise, two nonlinear blending schemes corresponding to viscosity and freezing point and four linear blending schemes corresponding to acid value, flash point, oxidation stability, and carbon residue are g...

Full description

Bibliographic Details
Main Authors: Min Yuan, Yu Li, Wenqiang Xu, Wei Cui
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/18/8375
_version_ 1797520396559319040
author Min Yuan
Yu Li
Wenqiang Xu
Wei Cui
author_facet Min Yuan
Yu Li
Wenqiang Xu
Wei Cui
author_sort Min Yuan
collection DOAJ
description Based on actual lubricating oil production data and the base oil performance indexes of an enterprise, two nonlinear blending schemes corresponding to viscosity and freezing point and four linear blending schemes corresponding to acid value, flash point, oxidation stability, and carbon residue are given in this paper. On the premise that the error of each index is less than 5%, a linear weighted multi-objective optimization model based on integer nonlinear programming considering cost and performance is established, and the lubricating oil blending scheme is obtained. The results show that the blending formula is simple in form and convenient in calculation, and that the overall consistency between the calculated value and the measured value is good. At the same time, the relative error of each performance index, except residual carbon, of the scheme with weight value of (0.5, 0.5) is far less than 5%. Although the performance index is slightly inferior to that of the scheme with a weight value of (0, 1), it is far higher than that of the scheme with a weight value of (1, 0). The linear weighted multi-objective optimization model based on integer nonlinear programming proposed in this paper can well-optimize the blending scheme of industrial lubricating oil, and can re-select different weight combinations according to the actual situation, providing good prospects for application.
first_indexed 2024-03-10T07:56:11Z
format Article
id doaj.art-7c2d8a747a2f4a6599844210692a6c5c
institution Directory Open Access Journal
issn 2076-3417
language English
last_indexed 2024-03-10T07:56:11Z
publishDate 2021-09-01
publisher MDPI AG
record_format Article
series Applied Sciences
spelling doaj.art-7c2d8a747a2f4a6599844210692a6c5c2023-11-22T11:51:43ZengMDPI AGApplied Sciences2076-34172021-09-011118837510.3390/app11188375Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear ProgrammingMin Yuan0Yu Li1Wenqiang Xu2Wei Cui3College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, ChinaBased on actual lubricating oil production data and the base oil performance indexes of an enterprise, two nonlinear blending schemes corresponding to viscosity and freezing point and four linear blending schemes corresponding to acid value, flash point, oxidation stability, and carbon residue are given in this paper. On the premise that the error of each index is less than 5%, a linear weighted multi-objective optimization model based on integer nonlinear programming considering cost and performance is established, and the lubricating oil blending scheme is obtained. The results show that the blending formula is simple in form and convenient in calculation, and that the overall consistency between the calculated value and the measured value is good. At the same time, the relative error of each performance index, except residual carbon, of the scheme with weight value of (0.5, 0.5) is far less than 5%. Although the performance index is slightly inferior to that of the scheme with a weight value of (0, 1), it is far higher than that of the scheme with a weight value of (1, 0). The linear weighted multi-objective optimization model based on integer nonlinear programming proposed in this paper can well-optimize the blending scheme of industrial lubricating oil, and can re-select different weight combinations according to the actual situation, providing good prospects for application.https://www.mdpi.com/2076-3417/11/18/8375lubricating oilinteger nonlinear programmingblending schememulti-objective optimization
spellingShingle Min Yuan
Yu Li
Wenqiang Xu
Wei Cui
Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming
Applied Sciences
lubricating oil
integer nonlinear programming
blending scheme
multi-objective optimization
title Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming
title_full Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming
title_fullStr Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming
title_full_unstemmed Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming
title_short Multi-Objective Optimization Model of Industrial Lubricants Based on Integer Nonlinear Programming
title_sort multi objective optimization model of industrial lubricants based on integer nonlinear programming
topic lubricating oil
integer nonlinear programming
blending scheme
multi-objective optimization
url https://www.mdpi.com/2076-3417/11/18/8375
work_keys_str_mv AT minyuan multiobjectiveoptimizationmodelofindustriallubricantsbasedonintegernonlinearprogramming
AT yuli multiobjectiveoptimizationmodelofindustriallubricantsbasedonintegernonlinearprogramming
AT wenqiangxu multiobjectiveoptimizationmodelofindustriallubricantsbasedonintegernonlinearprogramming
AT weicui multiobjectiveoptimizationmodelofindustriallubricantsbasedonintegernonlinearprogramming