An Ordered Flow Shop Scheduling Problem
Özet
The subject of the study is ordered flow shop scheduling problems which were first seen in the literature in the 1970s. The main objective is to get a fast and good solution. For the purpose of the study, firstly, the ordered flow shop scheduling problems were defined. Then, a heuristic method was suggested for the ordered flow shop scheduling problems and a sample problem was solved and discussed. A genetic algorithm (GA) based on the complexity property was developed. Full enumeration was applied to determine the optimal makespan values based on Smith’s rule because Smith had specified the conditions under which circumstances the permutation can be optimum. This study is one of the few studies in the literature to obtain optimum solutions up to 15 jobs ordered flow shop problems in a very short amount of time. The developed GA heuristic can also solve large size ordered flow shop scheduling problems very fast. The significant advantage of the proposed method is that, while Smith’s method rule not does not work with large size problems since it requires full enumeration to identify best solution to follow a convexity property where GA algorithm can find a good solution very fast.
Anahtar Kelimeler
- Scopus
- 1
- OpenAlex
- 2
Tam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Çakmak, Aslıhan | |
| dc.contributor.author | Ceylan, Zeynep | |
| dc.contributor.author | Bulkan, Serol | |
| dc.contributor.editor | Şen, Z. | |
| dc.contributor.editor | Uygun, O. | |
| dc.contributor.editor | Erden, C. | |
| dc.date.accessioned | 2026-10-27T23:47:41.512728728Z | |
| dc.date.available | 2026-10-27T23:47:41.512728728Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The subject of the study is ordered flow shop scheduling problems which were first seen in the literature in the 1970s. The main objective is to get a fast and good solution. For the purpose of the study, firstly, the ordered flow shop scheduling problems were defined. Then, a heuristic method was suggested for the ordered flow shop scheduling problems and a sample problem was solved and discussed. A genetic algorithm (GA) based on the complexity property was developed. Full enumeration was applied to determine the optimal makespan values based on Smith’s rule because Smith had specified the conditions under which circumstances the permutation can be optimum. This study is one of the few studies in the literature to obtain optimum solutions up to 15 jobs ordered flow shop problems in a very short amount of time. The developed GA heuristic can also solve large size ordered flow shop scheduling problems very fast. The significant advantage of the proposed method is that, while Smith’s method rule not does not work with large size problems since it requires full enumeration to identify best solution to follow a convexity property where GA algorithm can find a good solution very fast. | |
| dc.identifier.doi | 10.1007/978-981-99-6062-0_16 | |
| dc.identifier.endpage | 173 | |
| dc.identifier.isbn | 978-981996061-3 | |
| dc.identifier.issn | 2195-4356 | |
| dc.identifier.scopus | 2-s2.0-85174633180 | |
| dc.identifier.startpage | 161 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/kostu/10627 | |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media Deutschland GmbH | |
| dc.relation.conference | 12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 | |
| dc.relation.ispartof | Lecture Notes in Mechanical Engineering | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Convexity property | |
| dc.subject | Genetic Algorithms | |
| dc.subject | Makespan | |
| dc.subject | Ordered flowshop | |
| dc.subject | Scheduling | |
| dc.subject.other | Heuristic methods | |
| dc.subject.other | Machine shop practice | |
| dc.subject.other | Condition | |
| dc.subject.other | Convexity properties | |
| dc.subject.other | Flow shop scheduling problem | |
| dc.subject.other | Flow-shops | |
| dc.subject.other | Makespan | |
| dc.subject.other | Optimum solution | |
| dc.subject.other | Ordered flowshop | |
| dc.subject.other | Property | |
| dc.subject.other | Scheduling | |
| dc.subject.other | Value-based | |
| dc.subject.other | Genetic algorithms | |
| dc.title | An Ordered Flow Shop Scheduling Problem | |
| dc.type | Conference Object | |
| rdl.citation.openalex | 2 | |
| rdl.citation.scopus | 1 | |
| rdl.conference.date | 26 May 2023 through 28 May 2023 | |
| rdl.conference.place | Istanbul | |
| rdl.oa.status | closed | |
| rdl.scopus.quartile | Q4 | |
| rdl.source.index | SCOPUS |
