Ozturk, CemalettinÖrnek, Mustafa Arslan2023-06-162023-06-162014https://hdl.handle.net/20.500.14365/3994Computer and Industrial Engineering;et al.;Gaziantep University;Istanbul Commercial University;Journal of Intelligent Manufacturing Systems;Sakarya University, Department of Industrial EngineeringJoint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" 44th International Conference on Computers and Industrial Engineering, CIE 2014 and 9th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2014 -- 14 October 2014 through 16 October 2014 -- 110500In a so-called multi-period yarn dyeing and batching problem, we try to determine the optimal batching of customer orders to be dyed in dye machines in each shift to minimize total lateness and earliness costs. In addition to weight, production quantity and volume capacity of the machines, there is a set of technical dyeing interaction constraints such as flotte, colour types, colour percentages and chemical recipe of customer orders when yarns are immersed in a large vat of coloured water known as the dye-liquor that includes dyestuffs, plus a range of chemicals to assist the dyeing process in the same shift. Furthermore, because of multi-period multi-shift nature of the problem, there is a setup carryover restriction which enforces that from shift to shift the colours must be processed in the increasing degree of darkness, i.e., in technical terms, the colour percentage of the batch increases. To the best of our knowledge, there is no study in the literature to solve this combinatorial optimization problem. Hence, in this paper, we first develop a novel mixed integer programming (MIP) formulation and then, we present a case study in a worldwide known yarn manufacturing company.eninfo:eu-repo/semantics/closedAccessBatchingCase studyDyeingMixed integer programmingProduction planningColorCombinatorial optimizationDyeingIndicators (chemical)ManufactureOptimizationProduction controlWoolYarnBatchingCombinatorial optimization problemsMixed integer programmingMixed integer programming (MIP)Mixed integer programming modelProduction PlanningProduction quantityYarn manufacturingInteger programmingConference Object2-s2.0-84923884302