A Hybrid Stock optimization Approach for Inventory Management

Basit Öğe Kaydı
dc.authorscopusid55609423700
dc.authorscopusid57250617700
dc.authorscopusid57250272000
dc.authorscopusid57220810876
dc.authorscopusid56952927700
dc.contributor.authorÇimen, Egemen Berki
dc.contributor.authorKurban, İlknur
dc.contributor.authorSelmanoğlu, Özgür
dc.contributor.authorŞahin, Murat
dc.contributor.authorKılınç, Deniz
dc.date.accessioned2022-02-15T16:57:27Z
dc.date.available2022-02-15T16:57:27Z
dc.date.issued2021
dc.departmentBakırçay Üniversitesien_US
dc.description3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2021 -- 11 June 2021 through 13 June 2021 -- -- 171163en_US
dc.description.abstractModern world is rapidly evolving around knowledge and business that know how to use knowledge shows superiority. Thus, smart decision making becomes vital for the modern business world to achieve sustainability in life and business. Especially, with a world of scarce resources, utilizing knowledge would play critical not only today but also for future. Moreover, using knowledge is inevitable in supply chain and inventory management must be supported with smart algorithms and modern heuristics to avoid excessive inventory while fighting with stockout. Therefore, this study explores the opportunity for inventory planning with heuristics and tailored techniques as well as how to hybridize modern heuristics and tailored techniques. In this study, inventory optimization experiments are proposed to model spare part inventory management and find the best way to determine reorder amount to deal with shortage and excessive inventory. Four heuristics which are i) basic golden ratio, ii) simulated annealing, iii) statistical rule-based heuristic and iv) hybrid algorithm of simulated annealing and statistical rule-based heuristic are evaluated on existing spare part dataset with an example from real-life part supplier named Eldor. In this test case, 400 products are analyzed, and best reorder points and amounts are selected with the help of heuristics. Heuristics' main structures and parameters are adjusted for the problem's need and improvement on quality of results. Parameters are determined according to trial and error with experts' guidance on heuristics. The best result suggests 8% improvement on cost and 37% improvement on inventory load could achieve with the help of heuristics. These solutions are usable against even hard constraints like shortage. © 2021 IEEE.en_US
dc.identifier.doi10.1109/HORA52670.2021.9461353
dc.identifier.isbn9781665440585
dc.identifier.scopus2-s2.0-85114485145en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/HORA52670.2021.9461353
dc.identifier.urihttps://hdl.handle.net/20.500.14034/169
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.journalHORA 2021 - 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectInventory Managementen_US
dc.subjectSimulated Annealingen_US
dc.subjectStock optimizationen_US
dc.subjectAgricultural robotsen_US
dc.subjectDecision makingen_US
dc.subjectHuman computer interactionen_US
dc.subjectRoboticsen_US
dc.subjectSimulated annealingen_US
dc.subjectSupply chainsen_US
dc.subjectTechnology transferen_US
dc.subjectHard constraintsen_US
dc.subjectHybrid algorithmsen_US
dc.subjectInventory managementen_US
dc.subjectInventory optimizationen_US
dc.subjectInventory planningen_US
dc.subjectOptimization approachen_US
dc.subjectQuality of resultsen_US
dc.subjectStatistical rulesen_US
dc.subjectInventory controlen_US
dc.titleA Hybrid Stock optimization Approach for Inventory Managementen_US
dc.typeConference Objecten_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
[ X ]
İsim:
A Hybrid Stock optimization Approach for Inventory Management.pdf
Boyut:
310.52 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu
Bilgisayar Mühendisliği Bölümü Koleksiyonu