Robust multi-objective hybrid flow shop scheduling
Scheduling is an important decision-making process that aims to allocate limited resources to the jobs in a production process. Among scheduling problems, Hybrid Flow Shop (HFS) scheduling has good adaptability with most real world applications including innumerable cases of uncertainty of parameter...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Ayandegan Institute of Higher Education, Iran
2021-03-01
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| Series: | Journal of Applied Research on Industrial Engineering |
| Subjects: | |
| Online Access: | http://www.journal-aprie.com/article_122861.html |
| _version_ | 1818908757952823296 |
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| author | Behnaz Zanjani Maghsoud Amiri Payam Hanafizadeh Maziar Salahi |
| author_facet | Behnaz Zanjani Maghsoud Amiri Payam Hanafizadeh Maziar Salahi |
| author_sort | Behnaz Zanjani |
| collection | DOAJ |
| description | Scheduling is an important decision-making process that aims to allocate limited resources to the jobs in a production process. Among scheduling problems, Hybrid Flow Shop (HFS) scheduling has good adaptability with most real world applications including innumerable cases of uncertainty of parameters that would influence jobs processing when the schedule is executed. Thus a suitable scheduling model should take parameters uncertainty into account. The present study develops a multi-objective Robust Mixed-Integer Linear Programming (RMILP) model to accommodate the problem with the real-world conditions in which due date and processing time are assumed uncertain. The developed model is able to assign a set of jobs to available machines in order to obtain the best trade-off between two objectives including total tardiness and makespan under uncertain parameters. Fuzzy Goal Programming (FGP) is applied to solve this multi objective problem. Finally, to study and validate the efficiency of the developed RMILP model, some instances of different size are generated and solved using CPLEX solver of GAMS software under different uncertainty levels. Experimental results show that the developed model can find a solution to show the least modifications against uncertainty in processing time and due date in an HFS problem. |
| first_indexed | 2024-12-19T22:16:06Z |
| format | Article |
| id | doaj.art-96aa1a7acdda4e47b88aa486d0631f27 |
| institution | Directory Open Access Journal |
| issn | 2538-5100 |
| language | English |
| last_indexed | 2024-12-19T22:16:06Z |
| publishDate | 2021-03-01 |
| publisher | Ayandegan Institute of Higher Education, Iran |
| record_format | Article |
| series | Journal of Applied Research on Industrial Engineering |
| spelling | doaj.art-96aa1a7acdda4e47b88aa486d0631f272022-12-21T20:03:45ZengAyandegan Institute of Higher Education, IranJournal of Applied Research on Industrial Engineering2538-51002021-03-0181405510.22105/JARIE.2021.252651.1202Robust multi-objective hybrid flow shop schedulingBehnaz Zanjani0Maghsoud Amiri1Payam Hanafizadeh2Maziar Salahi3Department of Industrial Management, Faculty of Accounting and management, Allameh Tabataba'i University, Tehran, Iran.Department of Industrial Management, Faculty of Accounting and management, Allameh Tabataba'i University, Tehran, Iran.Department of Industrial Management, Faculty of Accounting and management, Allameh Tabataba'i University, Tehran, Iran.Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran.Scheduling is an important decision-making process that aims to allocate limited resources to the jobs in a production process. Among scheduling problems, Hybrid Flow Shop (HFS) scheduling has good adaptability with most real world applications including innumerable cases of uncertainty of parameters that would influence jobs processing when the schedule is executed. Thus a suitable scheduling model should take parameters uncertainty into account. The present study develops a multi-objective Robust Mixed-Integer Linear Programming (RMILP) model to accommodate the problem with the real-world conditions in which due date and processing time are assumed uncertain. The developed model is able to assign a set of jobs to available machines in order to obtain the best trade-off between two objectives including total tardiness and makespan under uncertain parameters. Fuzzy Goal Programming (FGP) is applied to solve this multi objective problem. Finally, to study and validate the efficiency of the developed RMILP model, some instances of different size are generated and solved using CPLEX solver of GAMS software under different uncertainty levels. Experimental results show that the developed model can find a solution to show the least modifications against uncertainty in processing time and due date in an HFS problem.http://www.journal-aprie.com/article_122861.htmlschedulinghybrid flow shop problemrobust optimizationfuzzy goal programming |
| spellingShingle | Behnaz Zanjani Maghsoud Amiri Payam Hanafizadeh Maziar Salahi Robust multi-objective hybrid flow shop scheduling Journal of Applied Research on Industrial Engineering scheduling hybrid flow shop problem robust optimization fuzzy goal programming |
| title | Robust multi-objective hybrid flow shop scheduling |
| title_full | Robust multi-objective hybrid flow shop scheduling |
| title_fullStr | Robust multi-objective hybrid flow shop scheduling |
| title_full_unstemmed | Robust multi-objective hybrid flow shop scheduling |
| title_short | Robust multi-objective hybrid flow shop scheduling |
| title_sort | robust multi objective hybrid flow shop scheduling |
| topic | scheduling hybrid flow shop problem robust optimization fuzzy goal programming |
| url | http://www.journal-aprie.com/article_122861.html |
| work_keys_str_mv | AT behnazzanjani robustmultiobjectivehybridflowshopscheduling AT maghsoudamiri robustmultiobjectivehybridflowshopscheduling AT payamhanafizadeh robustmultiobjectivehybridflowshopscheduling AT maziarsalahi robustmultiobjectivehybridflowshopscheduling |