@article{kilicaslan_ant_2023,
	title = {Ant {Colony} optimization application in bottleneck station scheduling},
	volume = {56},
	copyright = {All rights reserved},
	issn = {1474-0346},
	url = {https://www.sciencedirect.com/science/article/pii/S1474034623000976},
	doi = {10.1016/j.aei.2023.101969},
	abstract = {Finding optimal solutions to production planning and scheduling problems is crucial for surviving in a competitive environment and meeting customer expectations over time. Planning can become complicated in sectors with many different products such as tire production. This study focuses on the bottleneck problem caused by a machine called a Quadruplex Extruder in a tire factory. With this machine, rubber is extruded and transformed into a tread material product, which is critically important in some essential tire features, such as low rolling resistance and brake distance. This study aims to minimize the set-up times in production by optimizing the manufacturing order of the products produced in a quadruplex extruder machine using the Ant Colony Algorithm (ACA), a well-known metaheuristic method to solve polynomial optimization problems. In addition, the second version of the Lin–Kernighan–Helsgaun (LKH-2) algorithm was adapted to this problem. Manually prepared, LKH-2 and ACA-produced schedules were compared in terms of global efficiency. As a result, it has been shown that ACA can provide fast and suitable solutions for decision makers in production planning.},
	language = {en},
	urldate = {2023-04-14},
	journal = {Advanced Engineering Informatics},
	author = {Kılıçaslan, Emre and Demir, Halil Ibrahim and Kökçam, Abdullah Hulusi and Phanden, Rakesh Kumar and Erden, Caner},
	month = apr,
	year = {2023},
	keywords = {Ant Colony Algorithm, Bottleneck Station Scheduling, Lin–Kernighan–Helsgaun Algorithm, Optimization, Production Planning, Tire Production},
	pages = {101969},
}

{"_id":"sCGxPYGcwBCpa3B4Y","bibbaseid":"klaslan-demir-kkam-phanden-erden-antcolonyoptimizationapplicationinbottleneckstationscheduling-2023","author_short":["Kılıçaslan, E.","Demir, H. I.","Kökçam, A. H.","Phanden, R. K.","Erden, C."],"bibdata":{"bibtype":"article","type":"article","title":"Ant Colony optimization application in bottleneck station scheduling","volume":"56","copyright":"All rights reserved","issn":"1474-0346","url":"https://www.sciencedirect.com/science/article/pii/S1474034623000976","doi":"10.1016/j.aei.2023.101969","abstract":"Finding optimal solutions to production planning and scheduling problems is crucial for surviving in a competitive environment and meeting customer expectations over time. Planning can become complicated in sectors with many different products such as tire production. This study focuses on the bottleneck problem caused by a machine called a Quadruplex Extruder in a tire factory. With this machine, rubber is extruded and transformed into a tread material product, which is critically important in some essential tire features, such as low rolling resistance and brake distance. This study aims to minimize the set-up times in production by optimizing the manufacturing order of the products produced in a quadruplex extruder machine using the Ant Colony Algorithm (ACA), a well-known metaheuristic method to solve polynomial optimization problems. In addition, the second version of the Lin–Kernighan–Helsgaun (LKH-2) algorithm was adapted to this problem. Manually prepared, LKH-2 and ACA-produced schedules were compared in terms of global efficiency. As a result, it has been shown that ACA can provide fast and suitable solutions for decision makers in production planning.","language":"en","urldate":"2023-04-14","journal":"Advanced Engineering Informatics","author":[{"propositions":[],"lastnames":["Kılıçaslan"],"firstnames":["Emre"],"suffixes":[]},{"propositions":[],"lastnames":["Demir"],"firstnames":["Halil","Ibrahim"],"suffixes":[]},{"propositions":[],"lastnames":["Kökçam"],"firstnames":["Abdullah","Hulusi"],"suffixes":[]},{"propositions":[],"lastnames":["Phanden"],"firstnames":["Rakesh","Kumar"],"suffixes":[]},{"propositions":[],"lastnames":["Erden"],"firstnames":["Caner"],"suffixes":[]}],"month":"April","year":"2023","keywords":"Ant Colony Algorithm, Bottleneck Station Scheduling, Lin–Kernighan–Helsgaun Algorithm, Optimization, Production Planning, Tire Production","pages":"101969","bibtex":"@article{kilicaslan_ant_2023,\n\ttitle = {Ant {Colony} optimization application in bottleneck station scheduling},\n\tvolume = {56},\n\tcopyright = {All rights reserved},\n\tissn = {1474-0346},\n\turl = {https://www.sciencedirect.com/science/article/pii/S1474034623000976},\n\tdoi = {10.1016/j.aei.2023.101969},\n\tabstract = {Finding optimal solutions to production planning and scheduling problems is crucial for surviving in a competitive environment and meeting customer expectations over time. Planning can become complicated in sectors with many different products such as tire production. This study focuses on the bottleneck problem caused by a machine called a Quadruplex Extruder in a tire factory. With this machine, rubber is extruded and transformed into a tread material product, which is critically important in some essential tire features, such as low rolling resistance and brake distance. This study aims to minimize the set-up times in production by optimizing the manufacturing order of the products produced in a quadruplex extruder machine using the Ant Colony Algorithm (ACA), a well-known metaheuristic method to solve polynomial optimization problems. In addition, the second version of the Lin–Kernighan–Helsgaun (LKH-2) algorithm was adapted to this problem. Manually prepared, LKH-2 and ACA-produced schedules were compared in terms of global efficiency. 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