Strategy of changing cracking furnace feedstock based on improved group search optimization
The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified gro...
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| Published in | Chinese journal of chemical engineering Vol. 23; no. 1; pp. 181 - 191 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Elsevier B.V
2015
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| Abstract | The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the ＂excellent＂ infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained. |
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| AbstractList | The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the "excellent" infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained. The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the “excellent” infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained. Two kinds of feedstock are cracked in one cycle operation. Four products are considered, namely, ethylene, propylene, butadiene, and benzene. Their prices are known. The price of feedstock and operational costs are known. This scheduling model involves nonlinear object function and violation function. The improved GSO is used to solve the problem based on the previous model. Then, the best feedstock switchover can be achieved. For the feedstock NAP and HVGO, the feedstock is changed only once. The identified optimal solution can be achieved. NAP is cracked for 45days and NVGO for 28days. The yields of ethylene, propylene, and butadiene are considerably increased. Contrarily, the benzene yield is reduced. [Display omitted] The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the ＂excellent＂ infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained. |
| Author | Xiaoyu Nian Zhenlei Wang Feng Qian |
| AuthorAffiliation | Key Laboratory of Advanced Control and 0ptimization for Chemical Processes East China University of Science and Technology, Ministry of Education, Shanghai 200237, China |
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| CitedBy_id | crossref_primary_10_47836_pjst_29_2_06 crossref_primary_10_1016_j_energy_2018_01_159 crossref_primary_10_1016_j_energy_2020_119401 crossref_primary_10_1021_acs_iecr_0c00923 crossref_primary_10_2139_ssrn_4195975 crossref_primary_10_1016_j_energy_2019_06_035 crossref_primary_10_1016_j_fuel_2019_04_127 crossref_primary_10_1016_j_eswa_2022_119464 |
| Cites_doi | 10.1109/CEC.2006.1688455 10.1016/j.ins.2010.07.023 10.1021/ie050341r 10.1021/ie800741m 10.1021/ie048988j 10.1016/S1004-9541(13)60619-9 10.1016/S1004-9541(13)60472-8 10.1016/S1570-7946(00)80083-8 10.1002/aic.12224 10.1002/aic.690440714 10.1016/S0009-2509(00)00314-6 10.1109/TEVC.2007.902851 10.1021/ie050129n 10.1016/j.compchemeng.2006.09.001 10.1002/aic.10655 |
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| Keywords | Adaptive penalty function Scheduling of feedstock Double fitness values Group search optimizer Cracking furnace |
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| Notes | 11-3270/TQ Cracking furnace; Scheduling of feedstock; Group search optimizer; Adaptive penalty function; Double fitness values The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the ＂excellent＂ infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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| SubjectTerms | Adaptive penalty function Algorithms Chemical engineering Cracking furnace Double fitness values Feedstock Fracture mechanics Furnaces Group search optimizer Optimization Scheduling Scheduling of feedstock Searching 优化算法 加工时间 原料 引导搜索 生产调度 约束优化问题 裂解炉 金属温度 |
| Title | Strategy of changing cracking furnace feedstock based on improved group search optimization |
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