Ayca BingulNazlican GozacanAylin ÇalışkanCaliskan, AylinBingul, AycaChase, NazlicanN.M. Durakbasa , M.G. Gençyılmaz2025-10-0620239789819650583, 9783031991585, 9783031948886, 9789819667314, 9789811937156, 9783030703318, 9789811622779, 9789811969447, 9789819701056, 9789819748051978303124456821954364, 219543562195-435610.1007/978-3-031-24457-5_602-s2.0-85151118667https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151118667&doi=10.1007%2F978-3-031-24457-5_60&partnerID=40&md5=5b17ec4cc4bf601d7be66c605172b308https://gcris.yasar.edu.tr/handle/123456789/8576https://doi.org/10.1007/978-3-031-24457-5_60This study aims to optimize the cut-off dates in liner shipping to speed up the shipping process and allow customers to send their goods on time. This study contributes to the literature by assisting in determining the cut-off optimization in the liner shipping problem. Many explanatory variables have a positive effect resulting in the uncertainty of cut-off optimization in shipping. However there are apparent differences in cut-off dates across the shipping regions studied worldwide. The Arena Simulation Software was used to conduct this research. A flowchart was generated in line with the information provided by a liner operator to minimize all process times including the waiting time of the ship in port to estimate the best cut-off date for all processes. Then OptQuest an extension of the Arena software was used to optimize the simulation scenarios. © 2024 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessLiner Operator, Maritime Industry, Optimization, Simulation, Computer Software, Case-studies, Explanatory Variables, Liner Operator, Liner Shipping, Maritime Industry, Optimisations, Shipping Process, Simulation, Speed Up, Uncertainty, ShipsComputer software, Case-studies, Explanatory variables, Liner operator, Liner shipping, Maritime industry, Optimisations, Shipping process, Simulation, Speed up, Uncertainty, ShipsMaritime IndustryLiner OperatorOptimizationSimulationConference Object