A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem
Considering green scheduling and sustainable manufacturing, the energy-efficient hybrid flow shop scheduling problem (EHFSP) with a variable speed constraint is investigated, and a novel multi-population artificial bee colony algorithm (MPABC) is developed to minimize makespan, total tardiness and t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/13/12/2421 |
| _version_ | 1797500315105230848 |
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| author | Yandi Zuo Zhun Fan Tierui Zou Pan Wang |
| author_facet | Yandi Zuo Zhun Fan Tierui Zou Pan Wang |
| author_sort | Yandi Zuo |
| collection | DOAJ |
| description | Considering green scheduling and sustainable manufacturing, the energy-efficient hybrid flow shop scheduling problem (EHFSP) with a variable speed constraint is investigated, and a novel multi-population artificial bee colony algorithm (MPABC) is developed to minimize makespan, total tardiness and total energy consumption (TEC), simultaneously. It is necessary for manufacturers to fully understand the notion of symmetry in balancing economic and environmental indicators. To improve the search efficiency, the population was randomly categorized into a number of subpopulations, then several groups were constructed based on the quality of subpopulations. A different search strategy was executed in each group to maintain the population diversity. The historical optimization data were also used to enhance the quality of solutions. Finally, extensive experiments were conducted. The results demonstrate that MPABC can achieve an outstanding performance on three metrics <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>D</mi><mi>I</mi></mrow><mi>R</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>c</mi></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><mi>d</mi></mrow></semantics></math></inline-formula> for the considered EHFSP. |
| first_indexed | 2024-03-10T03:00:08Z |
| format | Article |
| id | doaj.art-8c367f70d5284e7cb620e43fbddf6810 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T03:00:08Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-8c367f70d5284e7cb620e43fbddf68102023-11-23T10:47:00ZengMDPI AGSymmetry2073-89942021-12-011312242110.3390/sym13122421A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling ProblemYandi Zuo0Zhun Fan1Tierui Zou2Pan Wang3School of Automation, Wuhan University of Technology, Wuhan 430062, ChinaDepartment of Electronic and Information Engineering, Shantou University, Shantou 515063, ChinaDepartment of Electrical & Computer Engineering, University of Florida, Gainesville, FL 32611, USASchool of Automation, Wuhan University of Technology, Wuhan 430062, ChinaConsidering green scheduling and sustainable manufacturing, the energy-efficient hybrid flow shop scheduling problem (EHFSP) with a variable speed constraint is investigated, and a novel multi-population artificial bee colony algorithm (MPABC) is developed to minimize makespan, total tardiness and total energy consumption (TEC), simultaneously. It is necessary for manufacturers to fully understand the notion of symmetry in balancing economic and environmental indicators. To improve the search efficiency, the population was randomly categorized into a number of subpopulations, then several groups were constructed based on the quality of subpopulations. A different search strategy was executed in each group to maintain the population diversity. The historical optimization data were also used to enhance the quality of solutions. Finally, extensive experiments were conducted. The results demonstrate that MPABC can achieve an outstanding performance on three metrics <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>D</mi><mi>I</mi></mrow><mi>R</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>c</mi></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><mi>d</mi></mrow></semantics></math></inline-formula> for the considered EHFSP.https://www.mdpi.com/2073-8994/13/12/2421energy-efficienthybrid flow shop schedulingartificial bee colonymulti-population |
| spellingShingle | Yandi Zuo Zhun Fan Tierui Zou Pan Wang A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem Symmetry energy-efficient hybrid flow shop scheduling artificial bee colony multi-population |
| title | A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem |
| title_full | A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem |
| title_fullStr | A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem |
| title_full_unstemmed | A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem |
| title_short | A Novel Multi-Population Artificial Bee Colony Algorithm for Energy-Efficient Hybrid Flow Shop Scheduling Problem |
| title_sort | novel multi population artificial bee colony algorithm for energy efficient hybrid flow shop scheduling problem |
| topic | energy-efficient hybrid flow shop scheduling artificial bee colony multi-population |
| url | https://www.mdpi.com/2073-8994/13/12/2421 |
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